EPA-600/8-86-023
August 1986
IDENTIFICATION, ASSESSMENT,
AND CONTROL OF FUGITIVE
PARTICULATE EMISSIONS
by
Chattan Cowherd Jr. and John S. Kinsey
Midwest Research Institute
425 Volker Boulevard
Kansas City, Missouri 64110
EPA Contract No. 68-02-3922
EPA Project Officer: Dale L Harmon
Air and Energy Engineering Research Laboratory
Research Triangle Park, North Carolina 27711
Prepared for.
U.S. Environmental Protection Agency
Office of Research and Development
Washington, D.C. 20460
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ABSTRACT
To assist control agency personnel and industry personnel in evaluating
fugitive emission control plans and in developing cost-effective control
strategies, the .U. S. Environmental Protection Agency has funded the prepara-
tion of a technical manual on the identification, assessment, and control of
fugitive particulate emissions. This manual's organizational structure follows
the steps to be undertaken in developing a cost- effective control strategy for
fugitive particulate emissions. The procedural steps are the same whether the
sources of interest are contained within a specific industrial facility or dis-
tributed over an air quality control jurisdiction.
The manual simmarizes the quality and extent of published performance
data for control systems applicable to open dust sources and process sources.
The scheme developed to rate performance data reflects the extent to which
a control efficiency value is based on mass emission measurement and re-
ported in enough detail for adequate validation. In addition to presenting a
cost analysis methodology, the manual identifies primary cost elements and
sources of oost data and presents a fully worked industrial example of cost-
effective control strategy development.
ii
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CONTENTS
Figures v
Tables vi
1.0 Introduction 1
1.1 Purpose of document 1
1.2 Scope of document 3
2.0 Source Identification 7
2.1 Definitions and examples 7
2.2 Source characteristics 12
2.3 Example industrial facility 13
References 16
3.0 Preparation of an Emissions Inventory .- 17
3.1 Published emission factors for estimating
emissions 18
3.2 Source testing methods for direct emission
measurement 22
3.3 Evaluation of control system performance 31
References 32
4.0 Identification of Control Alternatives 33
4.1 Preventive measures 34
4.2 Capture/removal methods 43
4.3 Applicability of controls to fugitive emissions
sources 51
4.4 Rating of performance data . . . 51
References 58
5.0 Estimation of Control System Performance—Open Sources 59
5.1 Stabilization of unpaved travel surfaces 61
5.2 Improvement of paved travel surfaces 76
5.3 Stabilization of piles/exposed areas 80
5.4 Enclosures 81
5.5 Wet suppression systems 83
5.6 Plume aftertreatment 86
5.7 Other open source controls 92
References 95
6.0 Estimation of Control System Performance—Process Sources . . . 101
6.1 Wet suppression systems 103
6.2 Enclosures 105
6.3 Capture/collection systems 105
6.4 Plume aftertreatment 109
6.5 Other process controls 112
References 112
iii
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CONTENTS (concluded)
7.0 Estimation of Control Costs and Cost-Effectiveness 115
7.1 Genera] cost methodology 116
7.2 Cost elements of fugitive emissions control
systems 125
7.3 Sources of cost data 136
References 137
8.0 Fugitive Emissions Control Strategy Development 139
8.1 Identify/classify fugitive emission sources 139
8.2 Prepare emissions inventory 141
8.3 Identify control alternatives 149
8.4 Estimate control efficiencies 149
8.5 Calculate cost and cost effectiveness 150
References 156
Appendix A - Estimation of Air Quality Impact/Improvement A-l
A.I Source-oriented models A-l
A.2 Receptor-oriented models A-4
References A-8
Appendix B - Glossary B-l
IV
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FIGURES
Number Page
1-1 Flow diagram for the identification, assessment, and
control of fugitive participate emissions 4
2-1 Simplified process flow diagram for a typical rock
crushing plant 14
3-1 Illustration of quasl-stack method 24
3-2 Illustration of roof monitor method 26
3-3 Illustration of upwind-downwind method 26
3-4 Illustration of exposure profiling method 28
3-5 Illustration of wind tunnel method 30
4-1 Diagram of a portable wind screen 37
4-2 Wet suppression system at a crusher discharge point. ... 39
4-3 Pressurized spray truck for application of chemical
dust suppressants 41
4-4 Diagrams of typical street cleaners 44
4-5 General types of capture devices (hoods) 46
4-6 Converter air curtain control system 49
4-7 Electrostatic foggers 50
4-8 Emissions quantification requirements for performance
evaluation of capture/collection system 57
5-1 Effect of vehicle speed, weight, and traffic rate on
control performance 62
5-2 Control efficiency decay for an initial application of
PetroTac® 67
5-3 Control efficiency decay for an initial application of
Coherex® 68
5-4 Control efficiency decay for an initial reapplication of
Coherex® 69
5-5 TSP control efficiency decay for light-duty traffic on
unpaved roads 70
5-6 Decay of control efficiency for LiquiDow® applied to
haul roads 71
5-7 Decay of control efficiency for Soil Sement® and Biocat-
Enzyme® applied to haul roads 72
5-8 Decay of control efficiency for Flambinder applied to
haul roads 73
5-9 Decay of control efficiency for Arco 2200® applied to
haul roads 74
5-10 Decay in control efficiency of latex binder applied to
coal storage piles 82
7-1 Graphical presentation of fugitive emission control
costs 122
8-1 Simplified process flow diagram for a typical rock
crushing plant 140
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TABLES
Number Page
2-1 Categories of Process Fugitive Sources 8
2-2 Generic Categories of Open Dust Sources 11
2-3 Open Dust Sources Associated with Construction and
Demolition 13
2-4 Source Identification for a Typical Rock Crushing Plant. . 15
4-1 Feasible Control Measures for Open Dust Sources 52
4-2 Process Fugitive Participate Emission Sources and
Feasible Control Technology 53
5-1 Classification of Tested Road Dust Suppressants 63
5-2 Summary of Major Unpaved Road Dust Suppressant Control
Efficiency Tests 65
5-3 Summary of Major Unpaved Road Dust Suppressant Control
Efficiency Decay Function Tests 66
5-4 Field Data on Watering Control Efficiency 75
5-5 Composite Control Effectiveness of Watering 77
5-6 Measured Single-Valued Particulate Control Efficiencies
for Vacuum Sweeping 79
5-7 Particulate Control Efficiency Decay Functions for Broom
Sweeping and Flushing 79
5-8 Summary of Available Control Efficiency Data for Wind
Fences/Barriers 84
5-9 Summary of Available Control Efficiency Data for Water
Sprays 87
5-10 Summary of Available Control Efficiency Data for Foam
Suppression ystems 88
5-11 Summary of Available Control Efficiency Data for Plume
Aftertreatment Systems (Open Dust Sources) 93
5-12 Literature References for Open Source Controls Where
No Test Data Are Available 95
6-1 Summary of Available Control Efficiency Data for Water
Sprays and Foam Suppression 104
6-2 Summary of Control Efficiency Data for Capture/
Collection Systems 110
6-3 Summary of Available Control Efficiency Data for Plume
Aftertreatment Systems (Process Sources) Ill
6-4 Literature References for Process Source Controls Where
No Test Data Are Available 112
7-1 Implementation Alternatives for Stabilization of an
Unpaved Road 118
7-2 Typical Values for Indirect Capital Costs 120
vi
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TABLES (concluded)
Number
7-3 Implementation Alternatives for Dust Suppressants Applied
to an Unpaved Road ................... 126
7-4 Implementation Alternatives for Street Cleaning ...... 127
7-5 Implementation Alternatives for Paving .......... 127
7-6 Implementation Alternatives for Wet Suppression ...... 128
7-7 Implementation Alternatives for Capture/Collection
Systems ......................... 129
7-8 Implementation Alternatives for Plume Aftertreatment
Systems ......................... 130
7-9 Capital Equipment and O&M Expenditure Items for Dust
Suppressant Systems (Open Sources) ........... 131
7-10 Capital Equipment and O&M Expenditure Items for Street
Cleaning ........................ 132
7-11 Capital Equipment and O&M Expenditure Items for Paving . . 132
7-12 Capital Equipment and O&M Expenditure Items for Wet
Suppression Systems (Process Sources) .......... 133
7-13 Capital Equipment and O&M Expenditure Items for Capture
Collection Systems ................... 134
7-14 * Capital and O&M Expenditures for Plume Aftertreatment
Systems ......................... 135
7-15 Published Sources of Fugitive Emission Control System
Cost Data ........................ 137
8-1 Plant and Process Data for Hypothetical Facility ..... 143
8-2 Cost Comparison for Two Selected Implementation
Scenarios ........................ 152
A-l Types of Receptor Models ................. A-5
vii
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SECTION 1
INTRODUCTION
Fugitive partlculate emissions are emitted by a wide variety of sources
both in the industrial and in the nonindustrial sectors. Fugitive emissions
refer to those air pollutants that enter the atmosphere without first pass-
ing through a stack or duct designed to direct or control their flow.
Fugitive particulate emission sources may be separated into two broad
categories: process sources and open dust sources. Process sources of fu-
gitive emissions are those associated with industrial operations that alter
the chemical or physical characteristics of a feed material. Examples are
emissions from charging and tapping of metallurgical furnaces and emissions
from crushing of mineral aggregate. Such emissions normally occur within
buildings and, unless captured, are discharged to the atmosphere through
forced or natural draft ventilation systems. Open dust sources entail the
entrainment of solid particles into the atmosphere by the forces of wind or
machinery acting on exposed materials. Open dust sources include industrial
sources associated with the open transport, storage, and transfer of raw,
intermediate, and waste materials, and nonindustrial sources such as unpaved
and paved public roads and construction activities.
1.1 PURPOSE OF DOCUMENT
To assist control agency personnel in evaluating fugitive emissions
control plans and to assist industry personnel in the development of cost-
effective control strategies, the U.S. Environmental Protection Agency has
funded the preparation of this technical guidance document on the identifi-
cation, assessment, and control of fugitive particulate emissions. The
document describes the procedures for developing a cost-effective strategy
for the control of fugitive particulate emissions within any specific plant
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or area setting. Also, it provides sources of data or in some cases actual
data needed to implement the procedures.
Within this document, cost-effectiveness is defined as the annualized
cost of control divided by the reduction in total annual particulate emis-
sions ($/Mg), as a result of the fugitive emissions control system being
employed. Control costs include the capital, operating, and maintenance
costs associated with the system over its useful life.
The particle size fractions cited in this manual include:
TP Total airborne particulate matter.
TSP Total suspended particulate matter, as represented approximately
by particles equal to or smaller than 30 pm in aerodynamic diam-
eter.
IP Inhalable particulate matter consisting of particles equal to or
smaller than 15 urn in aerodynamic diameter.
PM10 Particulate matter consisting of particles equal to or smaller
than 10 urn in aerodynamic diameter.
RP Respirable particulate matter consisting of particles equal to or
smaller than approximately 3.5 urn in aerodynamic diameter
FP Fine particulate matter consisting of particles equal to or
smaller than 2.5 pm in aerodynamic diameter.
Respirable particulate matter refers to the particle size fraction
penetrating the Dorr-Oliver cyclone used as a standard device for indus-
trial hygiene measurements. The cyclone has a 50% cut-point of about
3.5 umA when operated at 2 L/min and is the device chosen in the United
States to most closely simulate the penetration of dust into the lung.
Unless otherwise indicated, use of the term particulate emissions in
this document refers to the particle size fraction collected by the standard
high-volume sampler, which is the reference device for the existing National
Ambient Air Quality Standards for particulate matter. Although the standard
high-volume sampler does not have a sharp particle size cut-point for capture
of airborne particulate matter, an effective cut-point of 30 urn aerodynamic
diameter (umA) is frequently assigned. This particle size fraction is
normally referred to as total suspended particulate matter (TSP).
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1.2 SCOPE OF DOCUMENT
This document describes the recommended steps in developing a cost-
effective control strategy for specific sources of fugitive particulate
emissions.
Whether the sources of interest are contained within a specific indus-
trial facility or distributed over an air quality control jurisdiction, the
general procedure for control strategy development is the same. The steps
are as follows:
Step 1: Source identification.
Step 2: Preparation of an emissions inventory.
Step 3: Identification of control alternatives.
Step 4: Estimation of control system performance.
Step 5: Estimation of control costs.
Step 6: Selection of cost-effective controls.
Figure 1-1 graphically summarizes the procedure.
It is assumed that the need for reduction in emissions has been deter-
mined as required to achieve a desired net improvement in air quality or to
provide an offset for an increase in emissions from an expanding source
operation. The techniques for establishing relationships between air quality
and source emissions are described in Appendix A.
The organization of this document (i.e., chapter designations) reflects
an emphasis on control technology in relation to the other technical areas
associated with control strategy development. Also greater emphasis is
placed on open dust sources rather than process sources. This, in fact, is
consistent with the larger body of available data on the performance of open
dust source controls (focusing on controls applicable to unpaved roads).
Finally, although fugitive particulate emissions can be reduced by reducing
the extent of the source, this document focuses on the use of "add-on" con-
trols which do not affect the size or throughput of the source.
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Estimate Net
Air Quality
Improvement
Establish Need for
Control of Fugitive
Participate Emissions
Identify and
Classify Sources
I
Estimate Existing
Emissions from
Each Source
I
Rank Order
Most Significant
Sources
Determine Required
Emission Reductions
Finalize Control
Strategy
For Each Source
Identify Applicable
Control Options
Select Candidate
Controls for
Evaluation
Estimate Cost of
Each Control
Select Most
Cost-Effective
Control
Figure 1-1. Flow diagram for the identification, assessment,
and control of fugitive particulate emissions
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While a variety of control techniques applicable to sources of fugitive
particulate emissions are discussed in this document, control efficiency
values are specified only for those control options which have been tested
for effectiveness. However, the reader is referred to other review docu-
ments which present estimated values of control efficiency for control op-
tions which have no published performance data.
The chapter contents of this document are summarized as follows:
• Chapter 2 (Identification of Sources) defines the terms used to
identify sources of fugitive particulate emissions, describes
generic source categories, and classifies specific sources by
generic category within each major irfdustry in a matrix format.
• Chapter 3 (Preparation of an Emissions Inventory) presents a re-
view of the standard procedures used to develop an emissions in-
ventory and to determine the desired reduction in particulate emis-
sions from fugitive sources.
• Chapter 4 (Identification of Control Alternatives) identifies con-
trol alternatives by generic category and presents a matrix of
feasible control alternatives for specific sources within each
major industry.
• Chapter 5 (Estimation of Control System Performance—Open Sources)
documents and rates published performance data on open source con-
trols, identifies the parameters which affect control performance,
and compiles performance data for control alternatives applicable
to each generic source category.
• Chapter 6 (Estimation of Control System Performance—Process
Sources) documents and rates published performance data on pro-
cess source controls, identifies the parameters which affect
control performance, and compiles performance data for control
alternatives applicable to each generic source category.
• Chapter 7 (Estimation of Control Costs and Cost-Effectiveness)
describes estimation procedures for capital, operating, and
maintenance costs, and outlines the methodology for calculating
cost-effectiveness of continuously and periodically applied con-
trols.
• Chapter 8 (Hypothetical Case Study) presents a fully worked in-
dustrial example illustrating the procedural steps for control
strategy development, including the capital, operation, and
maintenance costs of representative controls.
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• Appendix A (Estimation of Air Quality Impact/Improvement) describes
the mathematical modeling techniques for assessing the air quality
impact of specific sources and for predicting the improvement in
air quality resulting from the implementation of specific controls.
• Appendix B is a glossary of terms used in this manual.
Other than complying with air pollution regulations, the control of
fugitive particulate emissions provides a number of tangible benefits. The
reduction of ground-level particulate concentrations within an industrial
complex prolongs the life of mechanical equipment and reduces the adversity
of the worker environment, thereby increasing production efficiency and
product quality. Finally, the industry that controls fugitive particulate
emissions that are otherwise visible to the public is perceived positively
by the surrounding community.
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SECTION 2
SOURCE IDENTIFICATION
The first step in the control strategy development procedure is the
identification of sources to be considered as candidates for control. This
section defines the basic terminology and lists the common types of fugitive
particulate emission sources. A glossary of terms further defining the vari-
ous types of fugitive sources and their associated controls is provided in
Appendix B.
2.1 DEFINITIONS AND EXAMPLES
Fugitive emissions refer to those air pollutants that (a) enter the at-
mosphere without first passing through a stack or duct designed to direct or
control their flow, or (b) leak from ducting systems. Sources of fugitive
particulate emissions may be separated into two broad categories: process
sources and open dust sources.
Process sources of fugitive emissions are those associated with indus-
trial operations that alter the chemical or physical characteristics of a
feed material. Examples are emissions from charging and tapping of metal-
lurgical furnaces and emissions from crushing of mineral aggregates. Such
emissions normally occur within buildings and, unless captured, are dis-
charged to the atmosphere through forced or natural draft ventilation sys-
tems. However, a process source of fugitive emissions can occur in the open
atmosphere (e.g., scrap metal cutting). The most significant industrial
process sources of fugitive particulate emissions are listed by industry in
Table 2-1.
Open dust sources are those that entail generation of fugitive emissions
of solid particles by the forces of wind or machinery acting on exposed
materials.
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TABLE 2-1. CATEGORIES OF PROCESS FUGITIVE SOURCES
Industry
Process source
Iron and Steel Plants
Ferrous Foundries
Primary Aluminum Production
Primary Copper Smelters
Primary Copper Smelters
Coal Crushing/Screening
Coke Ovens
Coke Oven Pushing
Sinter Machine Windbox
Sinter Machine Discharge
Sinter Cooler
Blast Furnace Charging
Blast Furnace Tapping
Slag Crushing/Screening
Molten Iron Transfer
BOF Charging/Tapping/Leaks
Open Hearth Charging/Tapping/Leaks
EAF Charging/Tapping/Leaks
Ingot Pouring
Continuous Casting
Scarfing
Furnace Charging/Tapping
Ductile Iron Inoculation (w/wo tundish
cover)
Pouring of Molten Metal
Casting Shakeout
Cooling/Cleaning/Finishing of Castings
Core Sand and Binder Mixing
Gri ndi ng/Screeni ng/Mixi ng/
Paste Production
Anode Baking
Electrolytic Reduction Cell
Refining and Casting
Roaster Charging
Roaster Leaks
Furnace Charging/Tapping/
Leaks
Slag Tapping/Handling
Converter Charging/Leaks
Blister Copper Tapping/Transfer
Copper Tapping/Casting
8
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TABLE 2-1. (continued)
Industry
Process source
Primary Lead Smelters
Primary Zinc Production
Secondary Aluminum Smelters
Secondary Lead Smelters
Secondary Zinc Production
Raw Material Mixing/Pelletizing
Sinter Machine Leaks
Sinter Return Handling
Sinter Machine Discharge/Screens
Sinter Crushing
Blast Furnace Charging/Tapping
Lead and Slag Pouring
Slag Cooling
Slag Granulator
Zinc Fuming Furnace Vents
Dross Kettle
Silver Retort Building
Lead Casting
Sinter Machine Windbox Discharge
Sinter Machine Discharge/Screens
Coke-Sinter Mixer
Furnace Tapping
Zinc Casting
Sweating Furnace
Smelting Furnace Charging/Tapping
Fluxing
Dross Handling and Cooling
Scrap Burning
Sweating Furnace Charging/Tapping
Reverb Furnace Charging/Tapping
Blast Furnace Charging/Tapping
Pot Furnace Charging/Tapping
Tapping of Holding Pot
Casting
Sweating Furnace Charging/Tapping
Hot Metal Transfer
Melting Furnace Charging/Tapping
Distillation Retort Charging/Tapping
Distillation Furnace Charging/Tapping
Casting
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TABLE 2-1. (concluded)
Industry
Process source
Secondary Copper, Brass/
Bronze Production
Ferroalloy Production
Cement Manufacturing
Lime Manufacturing
Rock Products
Asphalt Concrete Plants
Coal-Fired Power Plants
Grain Storage and Processing
Wood Products Industry
Mining
Sweating Furnace Charging/Tapping
Dryer Charging/Tapping
Melting Furnace Charging
Casting
Raw Materials Crushing/
Screening
Furnace Charging
Furnace Tapping
Casting
Limestone/Gypsum Crushing and
Screening
Coal Grinding
Limestone Crushing/Screening
Lime Screening/Conveying
Blasting
Primary Crushing/Screening
Secondary Crushing/Screening
Tertiary Crushing Screening
Aggregate Crushing/Screening
Pugmi11
Coal Pulverizing/Screening
Grain Cleaning
Grain Drying
Log Debarking/Sawing
Veneer Drying
Plywood Cutting
Plywood Sanding
Blasting
Crushing/Screening
10
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Open dust sources Include Industrial sources of particulate emissions asso-
ciated with the open transport, storage, and transfer of raw, intermediate,
and waste aggregate materials and nonindustrial sources such as unpaved
roads and parking lots, paved streets and highways, heavy construction
activities, and agricultural tilling. Generic categories of open dust
sources are listed in Table 2-2.
TABLE 2-2. GENERIC CATEGORIES OF OPEN DUST SOURCES
1. Unpaved Travel Surfaces
• Roads
• Parking lots and staging areas
• Storage piles
2. Paved Travel Surfaces
• Streets and highways
• Parking lots and staging areas
3. Exposed Areas (wind erosion)
• Storage piles
• Bare ground areas
4. Materials Handling
• Batch drop (dumping)
• Continuous drop (conveyor transfer, stacking)
• Pushing (dozing, grading, scraping)
• Tilling
The partially enclosed storage and transfer of materials to or from a
process operation do not fit well into either of the two categories of
fugitive particulate emissions defined above. Examples are partially en-
closed conveyor transfer stations and front-end loaders operating within
buildings. Nonetheless, partially enclosed materials handling operations
will be classified as open sources.
11
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2.2 SOURCE CHARACTERISTICS
Unlike ducted sources of participate emissions, which typically can be
characterized as continuously emitting, fugitive emission rates have a high
degree of temporal variability. Industrial process sources of fugitive par-
ti cul ate emissions are usually associated with batch operations, and emis-
sions fluctuate widely during the process cycle. Open dust sources within
industry also exhibit large fluctuations because of the sporadic nature of
materials handling operations and the effects of precipitation and wind on
the emissions potential.
In addition, fugitive emissions are characteristically diffuse in na-
ture and are discharged from a wide variety of source configurations. For
example, vehicles which entrain surface dust from industrial roads are best
represented as individual moving point sources (or as a line source for
high traffic density), while process fugitive emissions discharged from
building vents are usually depicted as area sources or virtual point
sources.
The various types of open dust sources listed in Table 2-2 can be found
either in an industrial facility or in the public sector. The mechanisms
of dust formation and thus the type of controls which can be applied in
either case are essentially the same. However, both the suitability and
cost-effectiveness associated with a specific control measure can change
significantly when applied in an industrial setting as compared to the same
control used for public sector sources. Therefore, the control strategies
used by public agencies often differ from those employed by industrial con-
cerns.
A number of public sector sources are perceived as single sources when
in actuality they are a series of different dust generating operations con-
fined to the same locality. Examples of this type of source include con-
struction and demolition activities, both of which involve dust generation
by various materials handling operations as well as vehicular traffic.
Table 2-3 lists the specific sources associated with construction and demo-
lition activities using the same general notation indicated in Tables 2-1
and 2-2 above.
12
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TABLE 2-3. OPEN DUST SOURCES ASSOCIATED WITH
CONSTRUCTION AND DEMOLITION
1. Construction Sites
Vehicular traffic on unpaved surfaces
Storage piles
Mud/dirt carryout onto paved travel surfaces
Exposed areas
Batch drop operations
Pushing (earth moving)
2. Demolition Sites
Vehicular traffic on unpaved surfaces
Storage piles
Mud/dirt carryout onto paved travel surfaces
Exposed areas
Batch drop operations
Pushing (dozer operation)
Blasting
One final public sector source worthy of note is agricultural tilling.
Tilling involves those operations associated with soil preparation, soil
maintenance, and crop harvesting activities. The emissions from these op-
erations are generally significant but are usually not controlled except by
operational modifications. Since add-on controls are not generally appli-
cable to agricultural tilling, such will not be covered in detail in this
document.
2.3 EXAMPLE INDUSTRIAL FACILITY
To illustrate the various types and classifications of sources found
in industrial facilities, Figure 2-1 shows a simplified process flow diagram
for a typical rock crushing plant. This particular example was selected
since it entails both process and open dust sources and has a well defined
process flow. Each source of fugitive particulate emissions in the facility
has been identified on the diagram and numbered in consecutive order. The
13
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Secondary -
Conveyor nneB
v_>
i In-Plant
Front-End ' T'a'"c
Loader
o
KEY: i Indicates fugitive emission
•«»—(a
point
^v ~\Bt-~viK' k '^BMar^-'B
.-' •.'•/.•S//S, ///.-/.'
Figure 2-1. Simplified process flow diagram for a typical rock crushing plant
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classification of each source using the definitions presented above is shown
in Table 2-4. This illustration should assist the environmental professional
in understanding the nomenclature used in subsequent sections of this docu-
ment. Diagrams for other processes can be found in the literature.2"5
TABLE 2-4. SOURCE IDENTIFICATION FOR A TYPICAL ROCK
CRUSHING PLANT3
Source.
ID No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Description of dust producing operation
Truck traffic on haul road
Truck dump
Primary crushing
Material transfer to conveyor
Material transfer to screen
Primary screening
Secondary crushing
Material transfer to conveyor
Material transfer to screen
Secondary screening
Tertiary crushing
Material transfer to conveyor
Material transfer to storage pile
Storage pile wind erosion
Loadout to trucks
Truck traffic leaving plant
Source
classification
Open dust
Open dust
Process
Open dust
Open dust
Process
Process
Open dust
Open dust
Process
Process
Open dust
Open dust
Open dust
Open dust
Open dust
a See Figure 2-1 for process flow.
From Figure 2-1.
15
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REFERENCES FOR SECTION 2
1. Cusclno, T. A., Jr., J. S. Kinsey, and R. Hackney. The Role of Agri-
cultural Practices in Fugitive Oust Emissions. NTIS No. PB81-219073,
California Air Resources Board, Sacramento, CA, June 1981.
2. Jutze, G. A., et al. Technical Guidance Document for Control of In-
dustrial Process Fugitive Particulate Emissions. EPA-450/3-77-010,
NTIS No. PB272288, U.S. Environmental Protection Agency, Research
Triangle Park, NC, March 1977.
3. Ohio Environmental Protection Agency. Reasonably Available Control
Measures for Fugitive Oust 'Sources. Columbus, OH, September 1980.
4. Oanielson, J. A. Air Pollution Engineering Manual. Second edition,
AP-40, NTIS No. PB225132, U.S. Environmental Protection Agency, Research
Triangle Park, NC, May 1973.
5. Mineral Processing Flowsheets. First printing, Denver Equipment
Company, Denver, CO, 1962.
16
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SECTION 3
PREPARATION FOR AN EMISSIONS INVENTORY
Once the fugitive participate emission sources within an industrial
facility or an air quality control region are identified, the next step is
to prepare a detailed emissions inventory. This will provide critical
information as to the types and locations of sources which account for most
of the existing fugitive participate emissions. The subsections below
describe the techniques commonly used for emission inventory development.
In developing an emissions inventory for a complex industrial facility
or an air quality control region, the large number of individual sources
and the diversity of source types make impractical the field measurement of
emissions at each point of release. In most cases the only feasible method
of determining source-by-source emissions is to estimate the typical emis-
sion rate for each of the source type and to adjust each estimate for the
size or activity of the source and the level of control.
Calculation of the estimated emission rate for a given source requires
data on source extent, uncontrolled emission factor, and control efficiency.
The mathematical expression for this calculation is as follows:
R = Me (1 - c) (3-1)
where:
R = estimated mass emission rate
M = source extent
e = uncontrolled emission factor, i.e., mass of uncontrolled
emissions per unit of source extent
c = fractional efficiency of control
17
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The source extent Is the appropriate measure of source size or level
of activity which is used to scale the uncontrolled emission factor to the
particular source in question. For process sources of fugitive particulate
emissions, the source extent is the production rate, i.e., the mass of prod-
uct per unit time. Similarly, the source extent of an open dust source en-
tailing a batch or continuous drop operation is the rate of mass through-
put.
For other categories of open dust sources, the source extent is related
to the area of the exposed surface which is disturbed by either wind or
mechanical forces. In the case of wind erosion, the source extent is the
area of credible surface. For emissions generated by mechanical disturbance,
source extent is also the area (or volume) of the material from which the
emissions emanate. For vehicle travel, the disturbed surface area is the
travel length times average daily traffic (AOT) count, with each vehicle
having a disturbance width equal to the width of a travel lane.
Normally, the "uncontrolled" emission factor incorporates the effects
of natural mitigation (e.g., rainfall). If anthropogenic control measures
(e.g., treating the surface with a chemical binder which forms an artificial
crust) are applied to the source, the uncontrolled emission factor must be
reduced to reflect the resulting fractional control.
3.1 PUBLISHED EMISSION FACTORS FOR ESTIMATING EMISSIONS
The document "Compilation of Air Pollutant Emission Factors" (AP-42),
published by the U.S. Environmental Protection Agency (EPA) since 1972, is
a compilation of emission factor reports for the most significant emission
source categories. Supplements to AP-42 have been published for both new
emission source categories and for updating existing emission source cate-
gories, as more information about sources and control of emissions has be-
come available.
Data obtained from source tests, material balance studies, and engi-
neering estimates are used to calculate the emission factors in AP-42.
These data are obtained from a variety of sources, including published
technical papers and reports, documented emission testing results, and per-
sonal communications. Some data sources provide complete details about
18
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their collecting and analyzing procedures, whereas other provide only
sketchy information in this regard.
Emission factors for sources of primary particulate emissions have been
compiled in AP-42. However, because the national effort to control indus-
trial sources of pollution has focused on emissions from ducted sources,
only a small portion of these factors apply to either process fugitive par-
ticulate emissions or open dust sources. In addition, because of the dif-
ficulty in quantifying the full particle size spectrum of particulate emis-
sions from fugitive sources, emission factors for these sources frequently
are poorly defined with regard to particle size.
3.1.1 Types of Emission Factors
The most reliable emission factors are based on field tests of repre-
sentative sources using a sound test methodology reported in enough detail
for adequate validation. Usually the emission factor for a given source
operation, as presented in a test report, is derived simply as the arithmetic
average of the individual emission factors calculated from each test of that
source. Frequently the range of individual emission factor values is also
presented.
As an alternative to the presentation of an emission factor as a single-
valued arithmetic mean, an emission factor may be presented in the form of
a predictive equation derived by regression analysis of test data. The pre-
dictive emission factor equation mathematically relates emissions to param-
eters which characterize source conditions. An emission factor equation is
useful if it is successful in "explaining" much of the observed variance in
emission factor values on the basis of corresponding variances in specific
source parameters. This enables more reliable estimates of source emissions
on a site-specific basis by allowing for correction of the emission factor
to specific source conditions.
In practice, the development of emission factor equations has been
limited to open dust source operations, each defined on the basis of a single
dust generation mechanism which crosses industry lines. An example would
be vehicular traffic on unpaved roads. To establish its applicability, each
generic equation has been developed from test data obtained in different
19
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industries. The correction parameters appearing in the predictive emission
factor equations for open dust sources fall into three categories:
1. Measures of sources activity or energy expended (for example, the
speed and weight of a vehicle traveling on an unpaved road).
2. Properties of the material being disturbed (for example, the content
of suspendable fines in the surface material on an unpaved road).
3. Climatic parameters (for example, number of precipitation-free days
per year on which emissions tend to be at a maximum).
3.1.2 Quality Rating Scheme
In selecting candidate emission factors for inclusion in AP-42, the
principal consideration centers around the reliability of each factor being
considered in relation to the reliability factors currently reported in
AP-42 for the same source. The emission factor rating system for AP-42
emission factors, was developed by the U.S. EPA, Office of Air Quality Plan-
ning and Standards (April 1980). This scheme entails the rating of test
data quality followed by the rating of the adequacy of the test data rela-
tive to the characterization of the uncontrolled emissions from the source
in question.
The rating system for a particular emission factor test data set is
based on the following data standards:
A - Tests performed by a sound methodology and reported in enough de-
tail for adequate validation. These tests are not necessarily
EPA reference method tests, although such reference methods are
certainly to be used as a guide.
B - Tests that are performed by a generally sound methodology but lack
enough detail for adequate validation.
C - Tests that are based on an untested or new methodology or that
lack a significant amount of background data.
D - Tests that are based on a generally unacceptable method but may
provide an order-of-magnitude value for the source.
20
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An A-rated test may be a source test, a material balance, or some other
methodology, as long as it is generally accepted as a sound method of mea-
suring emissions from that source.
In the ideal situation, a large number of A-rated source test data sets
representing a cross section of the industry are reduced to a single value
for each individual source by computing the arithmetic mean of each test
set. The emission factor is then computed by calculating the arithmetic
mean of the individual source values. Alternatively, regression analysis
is used to derive a predictive emission factor equation for the entire
A-rated test set. No B-, C-, or D-rated test sets are used in the calcula-
tion of the emission factor because the number of A-rated tests is suffi-
cient. This ideal method of calculating an emission factor is not always
possible because of lack of A-rated data.
If the number of A-rated tests is so limited that inclusion of B-rated
tests would improve the emission factor, then B-rated test data are included
in the compilation of the arithmetic mean. No C- or D-rated test data are
averaged with A- or B-rated test data. The rationale for inclusion of any
B-rated test data is documented in the background information.
If no A- or B-rated test series are available, the emission factor is
the arithmetic mean of the C- and D-rated test data. The C- and D-rated
test data are used only as a last resort, to provide an order-of-magnitude
value.
In AP-42, the reliability of these emission factors is indicated by an
overall Emission Factor Rating ranging from A (excellent) to E (poor). These
ratings take into account the type and amount of data from which the factors
were calculated, as follows:
• A - Excellent. Developed only from A-rated test data taken from
many randomly chosen facilities in the industry population. The
source category is specific enough to minimize variability within
the source category population.
• B - Above average. Developed only from A-rated test data from a
reasonable number of facilities. Although no specific bias is evi-
dent, it is not clear if the facilities tested represent a random
sample of the industry. As in the A rating, the source category is
specific enough to minimize variability within the source category
population.
21
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• C - Average. Developed only from A- and B-rated test data from a
reasonable number of facilities. Although no specific bias is evi-
dent, it'is not clear if the facilities tested represent a random
sample of the industry. As in the A rating, the source category is
specific enough to minimize variability within the source category
population.
• D - Below average. Developed only from A- and B-rated test data
from a small number of facilities, and there may be reason to sus-
pect that these facilities do not represent a random sample of the
industry. There also may be evidence of variability within the
source category population. Limitations on the use of the emission
factor should be footnoted.
• E - Poor. Developed from C- and 0-rated test data, and there may be
reason to suspect that the facilities tested do not represent a ran-
dom sample of the industry. There may be evidence of variability
within the source category population. Limitations on the use of
these factors are always footnoted.
Because the rating of an emission factor is subjective, the reasons for each
rating are documented in the background information.
3.2 SOURCE TESTING METHODS FOR DIRECT EMISSION MEASUREMENT
Rather than relying on the use of published emission factors, especially
for those sources of fugitive particulate emissions revealed as the most
significant in the preliminary emissions inventory, it may be desirable to
conduct source testing. This verifies the rates of uncontrolled emissions
from the most important sources and establishes the relative importance of
each of those sources. In addition, source testing would provide valuable
data on the emission characteristics of each source, which in turn would
aid considerably in selecting the most suitable control method for each
source.
This section summarizes the methods for field measurement of mass
emission rates and particle size distributions.
3.2.1 Mass Emissions Measurement
Fugitive particulate emission rates and particle size distributions
are difficult to quantify because of the diffuse and variable nature of such
22
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sources and the wide range of particle size involved (including particles
which deposit immediately adjacent to the source). Standard source testing
methods, which are designed for application to confined flows under steady-
state, forced-flow conditions, are not suitable for measurement of fugitive
emissions unless the plume can be drawn into a forced-flow system.
For field measurement of fugitive mass emissions, four basic techniques
have been defined:
1. The quasi-stack method involves capturing the entire participate
emissions stream with enclosures or hoods and applying conven-
tional source testing techniques to the confined flow.
2. The roof monitor method involves measurement of particulate con-
centrations and airflows across well defined building openings
such as roof monitors, ceiling vents, and windows, followed by
calculation of particulate mass flux exiting the building.
3. The upwind-downwind method involves measurement of upwind and
downwind particulate concentrations, utilizing ground based sam-
plers under known meteorological conditions, followed by calcula-
tion of source strength (mass emission rate) with atmospheric
dispersion equations.
4. The exposure profiling method involves simultaneous, multipoint
measurements of particulate concentration and wind speed over the
effective cross-section of the plume, followed by calculation of
net particulate mass flux through integration of the plume pro-
files.
5. The wind tunnel method involves the use of a portable open-floored
wind tunnel for HI situ measurement of emissions from representa-
tive surfaces under predetermined wind conditions.
Each of these methods will be discussed below.
Quasi-Stack Method (Figure 3-1)1
In effect, the quasi-stack method converts a fugitive emission source
to a conventional ducted source. Because it is usually impractical to en-
close an open dust source or capture its entire emissions plume, the quasi-
stack method is generally limited in applicability to process sources.
The quasi-stack method qualifies as a sound methodology only if evi-
dence is provided in the test report as to the fact that the enclosure or
23
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Figure 3-1. Illustration of quasi-stack method1
24
-------
hood is capturing the entire emissions stream without affecting the emission
rate. In addition, an accepted sampling technique (e.g., Method 5) must be
used to quantify the emission rate, taking steps to deal with special prob-
lems associated with highly fluctuating emissions.
Roof-Monitor Method (Figure 3-2)2
The roof monitor method is similar to the quasi-stack method in that
it utilizes the building ventilation system to direct the emissions stream
to the sampling location. Usually this method is practical only for high
temperature processes which produce buoyant plumes.
The roof-monitor method qualifies as a sound methodology only if flows
and concentrations can be adequately characterized within building discharge
openings. Also, it must be shown that plume interference from other sources
in the same building is not occurring. Finally, as with the quasi-stack
method, the test report must describe how special problems associated with
highly fluctuating emissions (and, in the case of natural ventilation,
fluctuating ambient winds) were dealt with.
Upwind/Downwind Method (Figure 3-3)s
The basic procedure of the upwind-downwind method involves the measure-
ment of particulate concentrations both upwind and downwind of the pollutant
source. The number of required upwind sampling instruments depend on the
isolability of the source operation of concern (i.e., the absence of inter-
ference from other sources upwind). Although at least five downwind parti-
culate samplers must be operated during a test, increasing the number of
downwind instruments improves the reliability in determining the emission
rate by providing better plume definition. In order to reasonably define
the plume emanating from a point source, instruments need to be located at
two downwind distances and three crosswind distances at a minimum. The same
sampling requirements pertain to line sources except that measurements at
multiple crosswind distances are not required.
After the concentration(s) measured upwind are subtracted from the
downwind concentrations, the net downwind concentrations are input to
dispersion equations (normally of the Gaussian type). The dispersion equa-
tions are used to back-calculate the particulate emission rate required to
25
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Fugitiv* (mission fiMMurwrant itatiom
in roof monitor for Mth fum
3g] Ground l«v»<
test itition
Figure 3-2. Illustration of roof monitor method2
Upwind
Sampler
Plume
Centerline
Figure 3-3. Illustration of upwind-downwind method3
26
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generate the pattern of downwind concentrations. A number of meteorological
parameters must be concurrently recorded for input to this dispersion equa-
tion. At a minimum the wind direction and speed must be recorded on-site.
Exposure Profiling Method (Figure 3-4)4
The exposure profiling method uses the profiling, concept that is the
basis for conventional (ducted) source testing, in much the same manner as
do the quasi-stack method and roof monitor methods. The difference is that
in the case of exposure profiling, the ambient wind directs the plume to
the sampling array. The passage of airborne particulate matter immediately
downwind of the source is measured directly by means of simultaneous multi-
point sampling of particulate concentration and wind velocity over the
effective cross section of the fugitive emissions plume. For measurement
of nonbuoyant fugitive emissions, profiling sampling heads are distributed
over a vertical network positioned just downwind (usually about 5 m) from
the source. Particulate sampling heads should be symmetrically distributed
over the concentrated portion of the plume containing about 90% of the total
mass flux (exposure). A vertical line grid of at least three samplers is
sufficient for measurement of emissions from line or moving point sources
while a two-dimensional array of at least five samplers is required for
quantification of fixed virtual point source emissions. At least one up-
wind sampler must be operated to measure background concentration, and wind
speed must be measured concurrently on-site.
Unlike the upwind/downwind method, exposure profiling uses a mass-
balance calculation scheme rather than requiring indirect calculation
through the application of a generalized atmospheric dispersion model.
The mass of airborne particulate matter emitted by the source is obtained
by spatial integration of distributed measurements of particulate flux,
after subtraction of the background contribution. The exposure is the
point value of the flux (concentration of airborne particulate accumu-
lated over the time of measurement).
27
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D Profiler Head (See below left)
O Cyclone/1mpactor (See below right)
~~\ Anemometer
Wind Vane
Profiler Head
with Motor
and Flow
Controller
Cyclone
Preseparator
with 5 Stage
Cascade
I mpactor
Figure 3-4. Illustration of exposure profiling method4
28
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Wind Tunnel Method (Figure 3-5)5
The wind tunnel method utilizes a portable pull-through wind tunnel
with an open-floored test section placed directly over the surface to be
tested. Air is drawn through the tunnel at controlled velocities. The
exit air stream from the test section passes through a circular duct fitted
with a sampling probe at the downstream end. Air is drawn through the probe
by a high-volume sampling train. This technique provides for precise study
of the wind-erosion process with minimal interference from background sources.
3.2.2 Particle Sizing
High-volume cascade impactors with glass fiber impaction substrates,
which are commonly used to measure mass size distribution of atmospheric
particulate, may be adapted for sizing of fugitive particulate emissions.
A cyclone preseparator (or other device) is needed to remove coarse parti-
cles which otherwise would be subject to particle bounce within the impactor
causing fine particle bias. Once again, the sampling intake should be
pointed into the wind and the sampling velocity adjusted to the mean local
wind speed by fitting the intake with a nozzle of appropriate size.
The EPA version of the dichotomous sampler, which is virtually free of
particle bounce problems, is useful for quantification of fine particle mass
concentrations. This sampler was designed with a symmetrical size-selective
inlet (having a particle size outpoint of 15 umA) which is insensitive to
wind speed or direction. However, this device operates at a low flow rate
(1 cu m/hr) yielding only 0.024 mg of sample in 24 hr for each 1.0 ug/m3 of
IP concentration. Thus, an analytical balance of high precision is required
to determine mass concentrations below and above the fine particulate (2.5 pm)
cutpoint (the minimum in the typical bimodal size distribution of atmospheric
particulate).
The size-selective inlet for a standard high-volume sampler is also
designed to capture particulate matter smaller than 15 umA. This unit is
much less wind sensitive than the dichotomous sampler but it does not pro-
vide a cutpoint at 2.5 urn. However, it can be adapted for use with a high
volume cascade impactor to define a mass size distribution of particles which
penetrate the sampler inlet. Recently, size-selective inlets with 10
29
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OJ
o
Flaxlbld Hose
Piessuie Gauges
Pilot Tuba Pod
Gasoline
Enoina
- Honeycomb
Figure 3-5. Illustration of wind tunnel method5
-------
outpoints have become available for both dichotomous samplers and high-
volume samplers.
Another particle sizing technique gaining some recent prominence is
microscopy. Microscopes used in particle sizing include optical or light
microscopes, transmission electron microscopes (TEM), and scanning electron
microscopes (SEM). Optical microscopy is useful in determining particle
size for particles greater than about 0.25 urn in diameter. Electron micro-
scopes provide the ability to size particles greater than about 0.001 urn in
diameter.
Of the many techniques available to size particles by their physical
dimensions as observed through the microscope, the most common approach is
the projected area technique. The particle size is set equal to the diameter
of a circle with the same area as the projected area of the particle. A
minimum of 300 particles is usually required in order to determine a size
distribution (with about 9 categories). Because this work requires several
tedious hours to perform manually, attempts to automate the process have
naturally arisen. Examples are the use automatic image analysis for optical
microscopy, and computer controlled scanning electron microscopy (CCSEM).
Both of these advances incorporate the projected area approach.
3.3 EVALUATION OF CONTROL SYSTEM PERFORMANCE
As in the case of uncontrolled emission factors, the efficiency of an
existing (or potential) control system can either be (a) established by
direct field measurements, or (b) estimated based on performance obtained
from the literature. However, this situation is one step more complex in
that determination of control performance requires knowledge of both the
uncontrolled and the controlled emission rates. This subject will be ex-
plored in detail at the end of Chapter 4 which identifies the various con-
trol alternatives for sources of fugitive particulate emissions.
31
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REFERENCES FOR SECTION 3
1. Kolnsberg, H. J., et al. Technical Manual for the Measurement of Fugi-
tive Emissions: Quasi-Stack Sampling Method for Industrial Fugitive
Emissions. EPA-600/2-76-089c, NTIS No. PB257848, U.S. Environmental
Protection Agency, Research Triangle Park, NC, May 1976.
2. Kenson, R. E. and P. T. Bartlett. Technical Manual for the Measurement
of Fugitive Emissions: Roof Monitor Sampling Method for Industrial Fu-
gitive Emissions. EPA-600/2-76-089b, NTIS No. PB257847, U.S. Environ-
mental Protection Agency, Research Triangle Park, NC, May 1976.
3. Axetell, K. Jr. and C. Cowherd, Jr. Improved Emission Factors for Fugi-
tive Dust from Western Surface Coal Mining Sources, Volumes I and II.
EPA-600/7-84-048, NTIS No. PB84-170802, U.S. Environmental Protection
Agency, Research Triangle Park, NC, March 1984.
4. Cowherd, C. Jr., et al. Development of Emissions Factors for Fugitive
Oust Sources. EPA-450/3-74-037, NTIS No. PB238262, U.S. Environmental
Protection Agency, Research Triangle Park, NC, June 1974.
5. Cuscino, T., G. Muleski and C. Cowherd, Jr. Iron and Steel Plant Open
Source Fugitive Emission Control Evaluation. EPA-600/2-83-110, NTIS
No. PB84-110568, U.S. Environmental Protection Agency, Research Triangle
Park, NC, October 1983.'
6. Kolnsberg, H. J. Technical Manual for Measurement of Fugitive Emis-
sions: Upwind/Downwind Sampling Method for Industrial Emissions. EPA-
600/2-76-089a, NTIS No. PB253092, U.S. Environmental Protection Agency,
Research Triangle Park, NC, April 1976.
32
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SECTION 4
IDENTIFICATION OF CONTROL ALTERNATIVES
Typically, there are several options for control of fugitive particu-
late emissions from any given source. This is clear from the mathematical
equation used to calculate the emission rate:
R = M e (1 - c)
where:
R = estimated mass emission rate
M = source extent
e = uncontrolled emission factor, i.e., mass of uncontrolled
emissions per unit of source extent
c = fractional efficiency of control
To begin with, because the uncontrolled emission rate is the product of the
source extent and uncontrolled emission factor, a reduction in either of
these two variables produces a proportional reduction in the uncontrolled
emission rate.
Although the reduction of source extent results in a highly predictable
reduction in the uncontrolled emission rate, such an approach in effect
usually requires a change in the process operation. Frequently, reduction
in the extent of one source may necessitate the increase in the extent of
another, as in the shifting of vehicle traffic from an unpaved road to a
paved road. The option of reducing source extent is beyond the scope of
this manual and will not be discussed further.
The reduction in the uncontrolled emission factor may be achieved by
process modifications (in the case of process sources) or by adjusted work
33
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practices (in the case of open sources). The degree of the possible reduc-
tion of the uncontrolled emission factor can be estimated from the known
dependence of the factor on source conditions that are subject to altera-
tion. For open dust sources, this information is embodied in the predic-
tive emission factor equations for fugitive dust sources as presented in
Section 11.2 of EPA's "Compilation of Air Pollutant Emission Factors"
(AP-42).
The reduction of source extent and the incorporation of process modi-
fications or adjusted work practices are preventive techniques for control
of fugitive particulate emissions. In addition, there are a variety of
"add-on" measures which can be used for (a) prevention of the creation
and/or release of particulate matter into the atmosphere, or (b) capture
and removal of the particles after they have become airborne.
Selection of suitable control methods depends on the mechanism(s) which
generate the particulate emissions and the specific source involved. The
methods used to control process sources of fugitive particulate emissions
generally take a much different approach from those applied to open dust
sources. Differences in source configuration, process requirements, and
emissions stream characteristics also affect selection of specific controls.
This section provides the information needed to identify feasible con-
trol techniques for specific sources of fugitive particulate emissions.
The basic characteristics of each type of control technique are described,
and the types of emission sources amenable to control by the techniques are
discussed. Control techniques applicable to the major sources of fugitive
particulate emissions defined in Section 2 are identified.
The section is divided into four parts. The first two parts describe
preventive and capture/removal control techniques, respectively. The third
part identifies the types of controls applicable to open dust and process
sources. Finally, the fourth part addresses the scheme used for quality
rating of control performance data.
4.1 PREVENTIVE MEASURES
Preventive measures include those measures which prevent or substan-
tially reduce the injection of particles into the surrounding air environment.
34
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Preventive measures are independent of whether the particulate is emitted
directly into the ambient air, or into the interior of a building. The main
types of preventive measures include:
• Passive enclosures (full or partial),
• Wet suppression,
• Stabilization of unpaved surfaces,
• Paved surface cleaning,
• Work practices, and
• Housekeeping.
Descriptions of control techniques within these five categories are pre-
sented below.
4.1.1 Passive Enclosures
A common preventive technique for the control of fugitive particulate
emissions is to either fully or partially enclose the source. Enclosures
preclude or inhibit particulate matter from becoming airborne due to the
disturbance created by ambient winds or by mechanical entrainment resulting
from the operation of the source itself. Enclosures also help contain those
emissions which are generated. Enclosures can consist of either some type
of permanent structure or a temporary arrangement. The particular type of
enclosure used is dependent on the individual source characteristics and
the degree of control required.
Permanent enclosures are designed to either partially or completely
enclose the source by the construction of a building or other structure.
Worker safety and housekeeping can become problems in the vicinity of the
fugitive emission source controlled by a passive (nonevacuated) enclosure.
Types of sources commonly controlled by total enclosures include aggregate
storage (bins rather than piles) and external conveyor transport.
Since temporary enclosures take many forms, they are difficult to
classify generically. Examples of temporary enclosures are flexible tar-
paulin covers over the hatchways of large ocean-going vessels during tjie
loading of grain, or flexible shrouds around truck loading spouts.
35
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A novel variation to the source enclosure method for the control of
fugitive participate emissions involves the application of porous wind
fences (also referred to as wind screens). Porous wind fences have been
shown to significantly reduce emissions from active storage piles and ex-
posed ground areas. The principle employed by wind screens is to provide a
sheltered region behind the fenceline where the mechanical turbulence gen-
erated by ambient winds is significantly reduced. The downwind extent of
the protected area is many times the physical height of the fence. This
sheltered region provides for both a reduction in the wind erosion potential
of the exposed surface in addition to allowing the gravitational settling of
the larger particles already airborne. The application of wind screens
along the leading edge of active storage piles seems to be one of the few
good control options which are available for this particular source. A di-
agram of one type of portable wind screen used at a coal-fired power plant
is shown in Figure 4-1.l
4.1.2 Wet Suppression
Wet suppression systems apply either water, a water solution of a
chemical agent, or a micron-sized foam to the surface of the particulate
generating material. This measure prevents or suppresses the fine particles
contained in that material from leaving the surface and becoming airborne.
If fine water sprays are used to control dust after it has become suspended,
this is referred to as plume aftertreatment. Plume aftertreatment (e.g.,
charged fog) is not a preventive measure but a capture/removal method as
discussed below.
The chemical agents used in wet suppression systems can be either sur-
factants or foaming agents for materials handling and processing operations
(e.g., crushers, conveyors) or various types of dust palliatives applied to
unpaved roads. In either case, the chemical agent acts to agglomerate and
bind the fines to the aggregate surface, thus eliminating or reducing its
emissions potential. Each major type of wet suppression method will be
described individually. "
Wet suppression systems using plain water have been utilized for many
years on a variety of sources such as crushing, screening, and materials
36
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Adapted from:
Reference 1
CO
Figure 4-1. Diagram of a portable wind screen1
-------
transfer operations, as well as unpaved roads. For most mechanical equip-
ment, wet suppression involves the use of one or more water sprays to wet
the material prior to processing. This technique is usually only temporar-
ily effective, requiring repeated application throughout the process flow.
An illustration of a wet suppression system used at a crusher discharge
point is shown in Figure 4-2.2
It should be noted that, in addition to possible freezing problems in
the winter, wet suppression with plain water can be used only on those bulk
materials which can tolerate a relatively high surface moisture content.
In the arid West, wet suppression is not always practical due to inadequate
water supplies.
In the case of unpaved roads and parking lots, water is generally ap-
plied to the surface by a truck or some other type of vehicle utilizing
either a pressurized or a gravity flow system. Again, watering of unpaved
roads is only a temporary measure, necessitating repeated application at
regular intervals.
To improve the overall control efficiency of wet dust suppression sys-
tems, wetting agents can be added to the water to reduce the surface ten-
sion. The additives allow particles to more easily penetrate the water
droplet and increase the number of droplets, thus increasing the surface
area and contact potential.
One of the more recently developed methods used to augment wet suppres-
sion techniques is the use of foam injection to control dust from materials
handling and processing operations. The foam is generated by adding a pro-
prietary surfactant compound to a relatively small quantity of water which is
then vigorously mixed to produce a small bubble, high energy foam in the 100-
to 200-um size range. The foam uses very little liquid volume and, when ap-
plied to the surface of a bulk material, wets the fines more effectively than
does untreated water. Foam has been used with good success for controlling
the emissions from belt transfer points, crushers, and storage pile load-in.
4.1.3 Stabilization of Unpaved Surfaces
Release of particulate from unpaved surfaces can be reduced or prevented
by stabilization of those surfaces. Sources which have been controlled in
38
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SUPPRESSANT
Figure 4-2. Wet suppression system at a crusher discharge point2
39
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this manner include unpaved roads and parking lots, active and inactive
storage piles, and open areas. Stabilizing mechanisms which have success-
fully employed include chemical, physical, and vegetative controls. Each
of these control types is described below.
The use of chemical dust suppressants for the control of fugitive emis-
sions from unpaved roads has received much attention in the past several
years. Chemical suppressants can be classified into six generic categories.
These are: (a) salts (i.e., CaCl2 and MgCl2); (b) lignin sulfonate; (c) wet-
ting agents; (d) latexes; (e) plastics; and (f) petroleum derivatives.
Salts, which are usually obtained from natural brine deposits, provide
dust control by absorbing and retaining moisture in the surface material.
Wetting agents enhance the mitigative effects of watering by lowering the
surface tension of water, thereby causing more rapid penetration into the
surface material. The remaining dust suppressants of both natural and syn-
thetic origin function by binding the fines to larger aggregates in the
surface material.
Chemical dust suppressants are generally applied to the road surface
as a water solution of the agent. The degree of control achieved is a direct
function of the application intensity, dilution ratio, and frequency (number
of applications/unit time) of the chemical applied to the surface and also
depends on the type and number of vehicles using the road. Chemical agents
have also been proven to be effective as crusting agents for inactive storage
piles and for the stabilization of exposed open areas. In both cases, the
chemical acts as a binder to reduce the wind erosion potential of the aggre-
gate surface. A typical pressurized spray truck used for the application of
chemical suppressants to unpaved surfaces is shown in Figure 4-3.3
Physical stabilization techniques can also be used for the control of
fugitive emissions from unpaved surfaces. Physical stabilization includes
any measure, such as compaction of fill material at construction and land
disposal sites, which physically reduces the emissions potential of a source
resulting from either mechanical disturbance or wind erosion.
The most notable form of physical stabilization of current interest
involves the use of civil engineering fabrics or "road carpet" for unpaved
roads. In practice, the road carpet fabric is laid on top of a properly
40
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SPRAY BAR
Figure 4-3. Pressurized spray truck for application of
chemical dust suppressants
prepared road base just below a layer of coarse aggregate (ballast). The
fabric sets up a physical barrier such that the fines (< 75 pro in diameter)
are prevented from contaminating the ballast layer. These smaller particles
are now no longer available for resuspension and saltation resulting from
the separation of the fines from the ballast. The fabric is also effective
in distributing the concentrated stress from heavy-wheeled traffic over a
wider area.
Vegetative stabilization involves the use of various species of flora
to control wind erosion from exposed surfaces. Vegetative techniques can
be used only when the material to be stabilized is inactive and will remain
so for an extended period of time. It is often difficult to establish a
vegetative cover over materials other than soil because their physical or
chemical characteristics are not conducive to plant growth. Resistant
strains which can tolerate the composition of the host material sometimes
must be developed.
41
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4.1.4 Paved Surface Cleaning
Other than housekeeping, the only method available to reduce the sur-
face loading of fine particles on paved roads is through some form of
street cleaning practice. Street sweeping does remove some debris from
the pavement thus preventing it from becoming airborne by the action of
passing vehicles; but it can also generate significant amounts of finer
particulate by the mechanical action used to collect the material.
The three major methods of street cleaning are mechanical cleaning,
vacuum cleaning, and flushing. Mechanical street sweepers utilize large
rotating brooms to lift the material from the pavement and discharge it into
a hopper for later disposal. Broom sweepers are usually effective in
picking up only relatively large debris, with a significant portion of the
surface material being suspended in the wake of the vehicle.
Vacuum sweepers remove the material from the street surface by drawing
a suction on a pickup head which entrains the particles in the moving air
stream. The debris is then deposited in a hopper, and the air is exhausted
to the atmosphere. Vacuum units also use gutter brooms to loosen and deflect
debris so that it can be picked up. They also have an additional broom which
loosens the street dirt and pushes it toward the vacuum nozzles where it is
drawn into the storage compartment. A filter system traps the dust and con-
fines it to the sweeper hopper.
The regenerative sweeper is a vacuum unit with certain significant
differences. Cleaning is accomplished by a pickup head with rubber dust
curtains at the front. The sweeper has a 9-ft cleaning width. A blower
directs a strong blast of air across the pickup head, and the suction from
the blower draws the debris into the hopper through a dust separator. Thus,
the air circulates continuously through the vacuum sweeper mechanism with
no air or dust exhausted to the atmosphere.
Street flushers hydraulically remove debris from the surface to the
gutter and eventually to the storm sewer system through the use of high
pressure water sprays. Water storage tanks on flushers vary in capacity
from 800 to 3,500 gal. Flushers have large nozzles, individually controlled,
which can be directed either toward the gutter or in a forward direction.
Water emerges from the nozzles at pressures of up to 100 psig. This pres-
sure is usually sufficient to scour most debris on the pavement. Flushers
42
-------
have numerous operational disadvantages including the consumption of large
quantities of water with the associated potential for water pollution prob-
lems. A diagram of both a typical broom sweeper and a regenerative air
sweeper is shown in Figure 4-4.3
4.1.5 Work Practices (Open Dust Sources)
Work practices may be used to reduce fugitive particulate emissions
from an open dust source by reducing the uncontrolled emission factor. Work
practices focus on the operation of equipment used to transport, store, and
transfer aggregate materials. The equipment related correction parameters
appearing in the1 AP-42 emission factor equations for open dust sources iden-
tify the work practice options. In the case of unpaved and paved travel
surface, emissions can be reduced by decreasing vehicle speed and weight.
For materials handling operations, emissions can be reduced by decreasing
drop height and by increasing bucket capacity. Finally, emissions from wind
erosion can be reduced by decreasing the size of the active area of a stor-
age pile or exposed ground surface.
4.1.6 Housekeeping
Housekeeping generally refers to the removal of exposed dust producing
materials on a periodic basis to reduce the potential for dust generation
through the action of wind or machinery. Examples of housekeeping measures
include: clean-up of spillage on travel surfaces (paved and unpaved); elim-
ination of mud/dirt carryout onto paved roads at construction and demolition
sites; and clean-up of material spillage at conveyor transfer points.
Any such method can be employed depending on the source, its operation,
and the type of dust-producing material involved. A detailed evaluation is
necessary on a case-by-case basis to determine what housekeeping measures
can be employed.
4.2 CAPTURE/REMOVAL METHODS
The second basic technique for the control of fugitive particulate
emissions includes those methods which capture or remove the particles af-
ter they have become airborne. Again, this classification is irrespective
43
-------
ELEVATOR
HOPPER
PICKUP BROOM-|
•ROTTER BROOM
(a) Four-wheeled broom sweeper
HOPPER
AUXILIARY ENGINE
z?r(P)
/ \
PICKUP HEAD GUTTER BROOM
(b) Regenerative air vacuum sweeper
Figure 4-4. Diagrams of typical street cleaners3
44
-------
of whether such emissions are generated inside or outside of a building.
The major types of capture/removal processes include:
• Capture and collection systems, and
• Plume aftertreatment.
The various methods in both categories are described below.
4.2.1 Capture and Collection Systems
Most industrial process fugitive emissions have traditionally been con-
trolled by capture/collection, or industrial ventilation systems. These
systems have three primary components: (a) a hood or enclosure to capture
emissions that escape from the process; (b) a dust collector that separates
entrained particulate from the captured gas stream; and (c) a ducting or
ventilation system to transport the gas stream from the hood or enclosure
to the air pollution control device.
A wide variety of capture mechanisms ranging from total enclosure of
the source, to mobile high velocity low volume (HVLV) hoods, to total build-
ing evacuation have been employed. Capture devices (or hoods) generally can
be classified as one of three types: enclosure, capture hood, or receiving
hood. Each type is illustrated in Figure 4-5.4
Enclosures, partial or complete, surround the source as much as possi-
ble without interfering with process operations. Their predominant feature
is that they prevent release of particulate to the atmosphere or working
environment. The enclosure is equipped with one or more takeoff ducts to
remove any particulate that is generated and to maintain a slight negative
pressure in the enclosure. Examples of enclosures include enclosed shake-
out operations in metal foundries, casings on bucket elevators used for
aggregate material transfer, and building evacuation for secondary furnace
control.
Capture hoods are located in such a manner that the process is external
to the hood. Emissions are actually released to the atmosphere or plant
environment and subsequently captured by the hood. Capture hoods have also
been referred to as exterior hoods by some authors.
45
-------
Fan
Adapted from:
Reference 4
Enclosures
Contaminants
rising from
hot process
Receiving Hoods
Capture Hoods
Figure 4-5. General types of capture devices (hoods)4
46
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The operating principle of the capture hood is based on capture velocity.
The control system must produce a sufficient air velocity at the emissions
source to draw the emitted particles to the hood and "capture" the emissions
stream. Examples of capture devices are side-draft hoods to capture secon-
dary electric arc furnace emissions, push/pull side-draft hoods to control
metal pouring emissions, and side-draft hoods control cleaning and finishing
emissions.
In the- case of receiving hoods, emissions from the process are also
released to the atmosphere or plant environment prior to entering the hood.
However, receiving hoods are designed to take advantage of the inherent
momentum of some emissions streams. This momentum is generally a result to
thermal buoyancy but also may be a result of inertia generated by the pro-
cess (e.g., a grinding plume). The system does not need to generate a
capture velocity, but it should be designed to exhaust a slightly greater
velocity from the hood than the process delivers. Examples of receiving
hoods include canopy hoods to capture secondary furnace emissions, close
capture hoods located above metal pouring operations, and grinding wheel
close capture hoods.
The selection of a suitable capture device is site-specific and depends
on both the operating and emissions characteristics of the source. Factors
influencing selection include location of the process with respect to other
plant operations, degree of process movement (if any), space needed for
worker or equipment access to the process, physical size of the operation
or process, and momentum of the particulate plume due to buoyancy or inertia
applied by the process.
Particulate matter is removed from the gas stream in capture/collection
systems by one of four generic types of air pollution control devices: me-
chanical collectors (or cyclones), wet scrubbers, fabric filters, and elec-
trostatic precipitators (ESPs). As with the capture device, selection of
the air pollution control device is site-specific, depending on such factors
as: degree of control required to meet regulations or enhance product re-
covery; availability of excess capacity from an existing control device;
feasibility of designing a common device for multiple sources; and various
characteristics of the emissions stream. Some of the more important
47
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emissions characteristics are particle size distribution, particle resis-
tivity, gas temperature, corrosivity, and chemical composition.
The simplest, and most often neglected, component of the industrial
ventilation system is the ductwork or transport system. The transport sys-
tem must be designed to maintain adequate transport velocities in the ducts
and be balanced with respect to pressure drop. Two of the most common causes
of malfunctions of capture/collection systems are plugging of the ductwork
because of.inadequate transport velocities and unbalanced ventilation systems
(from either poor design or improper operation) resulting in inadequate cap-
ture velocities or exhaust volumes at some processes.
A variation of the traditional capture/collection concept involves the
use of air curtains or jets. Air curtains are usually used in those indus-
trial processes which generate a buoyant plume to help isolate it and
enhance capture by the emissions control system. One such system is a
so-called "push/pull" arrangement. In such an arrangement, an air curtain
consisting of a series of jets is used to contain and direct the plume
toward some type of capture device. One such system is shown in Figure 4-6
for a copper converter.5
4.2.2 Plume Aftertreatment
Plume after-treatment refers to any system which injects fine water
droplets into a dust plume to capture and agglomerate the suspended particles
(by impaction and/or electrostatic attraction) to enhance gravitational
settling. Plume aftertreatment systems can use water sprays with or without
the addition of a chemical surfactant as well as with or without the applica-
tion of an electrostatic charge (charged fog).
Aftertreatment systems using plain water consist of one or more hydrau-
lic (pressure) or pneumatic (two-fluid) nozzles which create a spray of fine
water droplets. When sprayed into the dust plume, these droplets capture
and settle the suspended dust particles. This technique has been used exten-
sively for the control of respirable dust in underground mining and similar
operations conducted above ground.
-------
JCT sue
EXHAUST see
CUITAM
JET
•TO EXHAUST FAN
MTFIC UMLL—
TO GCHAU3T nit
Figure 4-6. Converter air curtain control system5
In the past several years, a novel means involving the use of electro-
statics has been developed to augment traditional water sprays for plume
aftertreatment. Most anthropogenically produced particles normally acquire
a slight electrostatic charge. By injecting a fog of oppositely charged
water droplets into the plumer a significant enhancement in the'capture and
removal process can be achieved.
An electrostatic charge can be applied to a water spray by either of
two means. Inouction charging applies an electrostatic charge to the drop-
lets by passing the spray through a ring which is isolated at a high voltage.
The alternative is to charge the water prior to atomization by direct con-
tact. Of the two methods, contact charging has proven to be much more ef-
fective in achieving a higher charge-to-mass ratio. Under heavy spray
conditions, induction charging tends to charge only those droplets on the
outside of the spray cone. Diagrams of electrostatic foggers using both
induction and contact charging are shown in Figure 4-7.6
49
-------
WATER
INPUT'S.
AIR "
INPUTA
POLARITY
LIGHTS
AIR PURGE
VALVE
INDUCTION
RING
SPRAY
NOZZLE
AIR AND FLUID CAPS
(a) Electrostatic fogger using induction charging
Air Fan
Noneonductlve
Air cone
Rotating
Seal,
DC Power
Supply
Water Reflecting
Baffle -
Nonconductive
Spinning Cup -
(b) Electrostatic fogger using contact charging
Figure 4-7. Electrostatic foggers6
Isolated
Water
Supply
50
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4.3 APPLICABILITY OF CONTROLS TO FUGITIVE EMISSIONS SOURCES
Open dust sources are generally controlled by preventive techniques
rather than capture/removal techniques. Typical measures used include pas-
sive enclosures, wet suppression, stabilization, and surface cleaning.
Table 4-1 identifies the types of control measures applicable to each of
the generic open dust source categories identified in Section 2.
Process fugitive sources can be controlled by either preventive or
capture/removal measures. Principal control measures include wet suppres-
sion, capture/collection systems, and plume aftertreatment. Table 4-2
identifies the types of control applicable to process fugitive emissions
sources.
4.4 RATING OF PERFORMANCE DATA
In evaluating the quality of performance data, the first step is to
locate the original source of the control efficiency value, whether it is
based on test data or simply estimation. This may require several steps
because of the practice of referencing a more recent (and presumably more
credible) document rather than the original source of the value. If the
value appears in a symposium paper, it is likely that there exists a more
comprehensive companion report which provides a more complete basis for the
quality evaluation.
The scheme used in this document for quality rating of control effi-
ciency values is similar to the A through E rating model developed by EPA
for AP-42 emission factors. The scheme entails the rating of test data
quality followed by the rating of the adequacy of the data relative to the
characterization of uncontrolled and controlled emissions.
To be assigned an A quality rating, a control efficiency value must be
based on mass emission tests performed by a sound methodology and reported
in enough detail for adequate validation. In addition, enough tests must
be performed at appropriate sampling points to quantify the average uncon-
trolled and controlled mass emission rates for the specific source/control
combination in question. Finally, values for the parameters needed to
characterize the source operation and the control system must be reported.
51
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TABLE 4-1. FEASIBLE CONTROL MEASURES FOR OPEN OUST SOURCES
en
ro
a Wet
Source category Enclosures suppression
Unpaved roads
Unpaved parking lots and staging areas
Slorage piles X
Paved streets and highways
Paved parking lots and staging areas
Exposed areas X
Batch drop operations'* X
Continuous drop operations X
Pushing (e.g., doling, grading,
scraping, etc. )
8 Includes full and partial enclosures as well
Includes both capture/collection systems and
X
X
X
X
X
X
X
as Mind fences.
plume
Fugitive [mission Control Measure
Chemical Physical Vegetative Surface Capture/
stabilization stabilization stabilization cleaning removal
X X
X X
X X
X
• X
XXX
X
X
X
c Includes operations such as front-end loaders,
shovels, etc.
stacking/reclaiming, etc.
-------
TABLE 4-2. PROCESS FUGITIVE PARTICIPATE EMISSION SOURCES AND FEASIBLE
CONTROL TECHNOLOGY
in
Industry
Iron and Steel Plants
Ferrous Foundries
Primary Aluminum Production
Prlnary Copper Smelters
Primary Copper Smelters
Uel
Process source suppression
Coal Crushing/Screening X
Coke Ovens
Coke Oven Pushing
Stnler Machine Wlndnon X
SlnteC Machine Discharge
Sinter Cooler
Blast Furnace Chaiglng
Blast Furnace lapping
Slag Crushing/Screening X
Molten Iron transfer
BOF Charglng/Tapplng/leaks
Open Hearth Charglng/Tapplng/leaks
EAF Charglng/Tapplng/leaks
Ingot Pouring
Continuous Casting
Scarfing
Furnace Charging/Tapping
Ductile Iron Inoculation
Pouring of Molten He til
Casting Shakeoul
Coollng/Cleantng/finlshing of Castings
Core Sand and Binder Nixing
Core Baking
Gr ind Ing/Screenl ng/Nixing/
Paste Production
Anode flaking
Electrolytic Reduction Cell
Refining and Casting
Roaster Charging
Roaster leaks
Furnace Charging/lapping/
Leaks
Slag Tapping/Handling
Converter Charging/Leaks
Blister Copper Tapping/transfer
Copper lipping/Casting
Control measure
Caplure/co 1 1 ec 1 1 on
. Receiving Capture Plume afler-
Fnc Insures hoods hoods trealoent
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
XXX
X
X X
X
X X
X
X X
X
X
X X
X
X
X
X
X
X
X
X
X
X
X
X X
X X
X
X
X
X
X
X
Water or water plus cheelcal additives
Includes full and/or partial enclosures with possible
evacuation to a dust collector
Host applications involve the use of canopy-type
receiving hoods.
-------
TABLE 4-2. (continued)
en
Control neasure
Industry
Primary Lead Shelters
Primary Zinc Production
Secondary Alunlnun Shelters
Secondary lead Smelters
Secondary 2lnc Production
Process source
Raw Material Mixing/Pencilling
Sinter Machine Leaks
Sinter Return Handling
Sinter Machine Discharge/Screens
Sinter Crushing
Blast Furnace Charging/Tapping
lead and Slag Pouring
Slag Cooling
Slag Granulator
Zinc F lining Furnace Vents
Dross Kettle
Silver Retort Building
lead Casting
Sinter Machine Wlndbox Discharge
Sinter Machine Discharge/Screens
Coke-Sinter Mixer
Furnace Tapping
Zinc Casting
Sweating Furnace
Saeltlng Furnace Charging/lapping
Fluxing
Dross Handling and Cooling
Scrap Burning
Sweating Furnace Charging/lapping
Reverb Furnace Charging/lapping
Blast Furnace Charging/lapping
Pot Furnace Charging/lapping
lapping of Holding Pot
Casting
Sweating Furnace Charging/Tapping
Hot Metal Transfer
Melting Furnace Charging/Tapping
Distillation Retort Charging/lapping
Distillation Furnace Charging/Tapping
Casting
Wel a b
suppression Enclosures
X
X
X
X
X
X
X X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Capture/collection
Receiving Capture Pluae after-
hoods hoods treatment
X
X
X
X
X X
X
X
X
X
X
X
X
X
X
X
X
X
X X
X
X
X
X
X
X
X
X
X
X
X
X
Water or water plus chealcal additives
Includes full and/or partial enclosuies with possible
evacuation to a dust collector
Most applications Involve the use of canopy-type
receiving hoods.
-------
TABLE 4-2. (concluded)
in
in
Control measure
Capture/col lection
Industry
Secondary Copper, Brass/
Qronze Production
Ferroalloy Production
Cement Manufacturing
Lime Manufacturing
Rock Products
Asphalt Concrete Plants
Coal-Fired Power Plants
Grain Storage and Processing
Wood Products
Mining
Process source
Sweating Furnace Charging/lapping
Dryer Charging/Tapping
Melting Furnace Charging
Casting
Raw Materials Crushing/
Screening
Furnace Charging
Furnace Tapping
Casting
Limestone/Gypsum Crushing and
Screening
Coal Grinding
Limestone Crushing/Screening
Lime Screening/Conveying
Primary Crushing/Screening
Secondary Crushing/Screening
Tertiary Crushing Screening
Aggregate Crushing/Screening
Coal Pulverizing/Screening
Grain Cleaning
Grain Drying
Log Debarking/Sawing
Veneer Drying
Plywood Cutting
Plywood Sanding
Blasting
Crush dig/Screen ing
Wet
suppress Ion
X
X
X
X
X
X
X
X
X
X
X
Enclosures
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Receiving
hoods
X
X
X
X
X
X
X
X
Capture
hoods
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Plume after-
treatment
X
X
X
X
X
X
X
X
X
X
X
X
X
Water or water plus chemical additives.
Includes full and/or partial enclosures with possible
evacuation to a dust collector
Most applications involve the use of canopy-type
receiving hoods.
-------
At the other extreme, a control efficiency value based only on estimation
is assigned an E Tating.
In the case of a capture/collection system applied to a process source
of fugitive emissions, -the controlled emissions are made of: (a) that por-
tion of the uncontrolled emissions which are not captured, plus (b) that
portion of the uncontrolled emissions which are captured but not collected.
This is illustrated in Figure 4-8 for a canopy hood. Frequently testing is
performed at the inlet and outlet of the collection device, but the data
are insufficient to determine the overall control efficiency.
With regard to sufficiency in the number of tests required to reliably
quantify the average emission rate (controlled or uncontrolled) at a sampl-
ing location, this depends on the variability of the emission rate. Tradi-
tionally, three tests of a process source represent the minimum requirement
for reliable quantification.
For preventive control measures and plume aftertreatment, either of
two study designs may be used to determine the control efficiency. A Type 1
design entails the measurement of source emissions with and without the
application of control. In a Type 2 design, emissions from identical sources
are measured, one with control and other without control. It must be shown
that the two sources are identical in terms of their uncontrolled emissions.
The question of the representativeness of the source operation and con-
trol system being tested is germane only if a widely applicable control ef-
ficiency value is being sought. In such a case, the value should be based
on tests of several source/control facilities of the same type which typify
a particular industry. However, unless the variability of the determined
control efficiency values from one facility to another is small, it is pre-
ferable to list each value separately with the corresponding source/control
parameters. This procedure opens the possibility of developing a statisti-
cal performance model which mathematically relates the observed variance in
control efficiency to the variances in the source/control parameters.
In Chapters 5 and 6, the following protocol is used for presenting
published control efficiency values (in tabular form):
56
-------
Not
Captured
Collection
Device
Captured
Capture
Device
Captured
but not
Collected
Uncontrolled
Control Efficiency (%)
where rh-i = tr\z 4- m4
" (r*
x 100
Figure 4-8. Emissions quantification requirements for performance
evaluation of capture/collection system
57
-------
1. For a given source and control system combination, each control
efficiency value is presented with a reliability rating (A through
E) based on the degree to which the value was determined from a
sound, adequately documented testing program.
2. To properly define the representativeness (applicability) of a
control efficiency value, the distinguishing source emission and
control system parameters are specified with the efficiency value.
The reader is cautioned that the reliability rating must be re-
duced if the control efficiency value is applied to a source/con-
trol combination in the same category but with one or more param-
eters which differ significantly from those specified. More than
one control efficiency value are presented for the same generic
source/control combination,-if the specified source/control param-
eters are not equivalent for the available efficiency values.
3. Each control efficiency value is referenced to the original source
of test data or rationale for an estimate. This approach elimi-
nates the confusion which results from referencing more recent
documents that may (or may not) reference the original source of
the control efficiency value. As a general rule, values which
cannot be traced to an original reference documents that are
accessible to the public, are not listed.
REFERENCES FOR SECTION 4
1. Radkey, R. L., and P. B. MacCready. A Study of the Use of Porous Wind
Fences to Reduce Particulate Emissions at the Mohave Generating Sta-
tion. AV-R-9563, AeroVironment, Inc., Pasadena, CA, 1980.
2. Ohio Environmental Protection Agency. Reasonably Available Control
Measures for Fugitive Oust Sources. Columbus, OH, September 1980.
3. Duncan, M., et al. Performance Evaluation of an Improved Street
Sweeper. EPA-600/7-85-008, NTIS No. PB85-169845, U.S. Environmental
Protection Agency, Research Triangle Park, NC, March 1985.
4. McDermott, H. J. Handbook of Ventilation for Contaminant Control.
Fifth Printing, Ann Arbor Science Publishers, Inc., Ann Arbor, MI,
1983.
5. Kashdan, E. R., et al. Technical Manual: Hood System Capture of Pro-
cess Fugitive Particulate Emissions. EPA-600/7-86-016, NTIS No. PB86-
190444, U.S. Environmental Protection Agency, Research Triangle Park,
NC, April 1986.
6. McCoy, J., et al. Evaluation of Charged Water Sprays for Dust Control.
Contract H0212012, U.S. Bureau of Mines, Washington, D.C., January
1983.
58
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SECTION 5
ESTIMATION OF CONTROL SYSTEM PERFORMANCE
— OPEN SOURCES
The performance capability of an open dust source control system depends
on a variety of parameters related to (a) properties of the emitting mate-
rial, (b) characteristics of the equipment involved in the source operation,
(c) climatic factors, and (d) the "intensity" of control application. Fur-
thermore, because of site-to-site differences in most of these parameters,
the performance of a given control system can be expected to vary signifi-
cantly from one application to another. Therefore, in utilizing the control
efficiency data presented in this section for control performance assess-
ment, care must be taken to document the source and control parameters tied
to each control efficiency data set.
The alternative approaches available for the control of open dust
sources include:
1. Stabilization of Unpaved Travel Surfaces
• Wet suppression
• Chemical stabilization
• Physical stabilization
• Paving
2. Improvement of Paved Travel Surfaces
• Surface cleaning
• Resurfacing
• Reduction of track-on
3. Stabilization of Piles/Exposed Areas
• Wet suppression
• Chemical stabilization
• Physical-stabilization
59
-------
4. Enclosure of Piles/Exposed Areas or Materials Handling
• Passive enclosures (including wind fences)
• Active enclosures
5. Wet Suppression for Materials Handling
6. Plume Aftertreatment for Materials Handling
• Fine water sprays
• Charged fog
The first three of these categories and passive enclosures are preventive
measures, whereas active enclosures and plume aftertreatraent are capture/
removal methods.
Most of the preventive measures involve periodic rather than continuous
control application. Familiar examples are the watering of unpaved travel
surfaces and the cleaning of paved travel surfaces. The resultant control
efficiency follows a cyclic pattern, decaying in time from the highest value
immediately after application. Because of the finite durability of these
control techniques, ranging from hours to months, it is essential to relate
an average efficiency value to a frequency of application. For measures of
extended durability such as paving, the application program required to sus-
tain control effectiveness should be indicated. One likely pitfall to be
avoided is the use of field data collected soon after control measure appli-
cation to represent the average control efficiency over the lifetime of the
measure.
For a periodically applied control measure, the most representative
value of control efficiency is the time average, given by:
C(T) = | QJ c(t) dt (5-1)
where:
C(T) = average control efficiency during period of T days between
application (percent)
c(t) = instantaneous control efficiency at t days after application
(percent), where t I T
60
-------
It must be emphasized that the rate of control efficiency decay is heavily
dependent upon the source and control variables discussed in the following
sections.
5.1 STABILIZATION OF UNPAVED TRAVEL SURFACES
5.1.1 Design Considerations
Control efficiency values for unpaved road dust controls can be
affected by four categories of variables: (a) control application param-
eters; (b) vehicle characteristics; (c) properties of the surface to be
treated; and (d) climatic factors. Each of these categories will be dis-
cussed in the following paragraphs.
The control application parameters affecting control performance of
chemical dust suppressants are: (a) application intensity; (b) application
frequency; (c) dilution ratio; and (d) application procedure. Application
intensity is the volume of diluted solution placed on the surface per unit
area of surface (e.g., L/m2 or gal/yd2). The higher the intensity, the
higher the anticipated control efficiency. However, this relationship
applies only to a point, because too intense an application will begin to
run off the surface. The point where runoff occurs depends on the slope
and porosity of the surface. Application frequency is the number of appli-
cations per unit of time. The dilution ratio is the volume of chemical
concentrate divided by the volume of water (e.g., 1:7 dilution ratio = 1
part chemical to 7 parts water).
The decay in control efficiency of a chemical dust suppressant occurs
largely because vehicles traveling over the road surface impart energy to
the treated surface which breaks the adhesive bonds that keep fine particles
on the surface from becoming airborne. Figure 5-1 is a general plot por-
traying the change in rate of decay of the instantaneous control efficiency
for a chemical suppressant applied to an unpaved road as a function of ve-
hicle speed, weight, and traffic rate. As indicated, an increase in vehicle
weight and speed serves to accelerate the decay in efficiency for chemical
treatment of unpaved roads.
Any surface characteristics which contribute to the breaking of a sur-
face crust will adversely affect the control efficiency. For example, the
61
-------
100
o
UJ
2
1
O
Increasing Vehicle
Speed, Weight, and
Traffic Rate
Time After Application
Figure 5-1. Effect of vehicle speed, weight, and traffic
rate on control performance
structural characteristics of an unpaved road affect the performance of
chemical controls. These characteristics are: (a) combined subgrade and
base bearing strength, as measured by the California Bearing Ratio (CBR);
(b) amount of fine material (silt and clay) on the surface of the road; and
(c) the friability of the road surface material. Low bearing strength
causes the road to flex and rut in spots with the passage of heavy trucks;
this destroys the compacted surface enhanced by the chemical treatment. A
minimum amount of fine material in the wearing surface is needed to provide
the chemical binder with the particle surface area necessary for effective
interparticle bonding. Finally, the larger particles of a friable wearing
surface material simply break up under the weight of the vehicles and cover
the treated road with a layer of untreated dust.
-------
For the most part, adverse weather, accelerates the decay of control
performance. For example, freeze-thaw cycles break up the crust formed by
chemical binding agents; heavy precipitation washes away water-soluble
chemical treatments like lignin sulfonates; and intense solar radiation dries
out watered surfaces. On the other hand, light precipitation might improve
the efficiency of water extenders and hygroscopic chemicals like calcium
chloride.
5.1.2 Performance Data
The control of dust emissions from unpaved roads has received the widest
attention in the literature (see Table 5-1). Exposure profiling and upwind/
downwind sampling have been used to measure control efficiencies for watering
TABLE 5-1. CLASSIFICATION OF TESTED ROAD DUST SUPPRESSANTS
Dust
suppressant
category
Petroleum-based
Lignosulfonates
Salts
Polymer
Surfactant
Trade Number of valid
name controlled tests
Petro Tac
Coherex
Arcote 220
Arco 2200
Arco 2400
Lignosite
Trex
Flambinder
Peladow
Liquidow
Dustgard
Oil Well Brine
Soil Sement
Biocat
8
124a
4a
20
91
73
3
4a + 28
1
34 b
11 (17)°
4
24
3
Reference
numbers
1-3,
1-6
4
8
7
7
10
4
9
8
7
4
8
8
Arcote 220/Flambinder mixture.
Numbers without parentheses represent TSP and numbers in
parentheses represent respirable particulate.
63
-------
and for a range of chemicals which bind the surface material or increase
its capacity for moisture retention. Tables 5-2 and 5-3 summarize the mea-
sured performance data for chemical dust suppressants.
The observed control efficiency decay functions for several dust sup-
pressants, are shown in Figures 5-2 to 5-9. These functions are properly
expressed in terms of vehicle passes rather than time because vehicle traf-
fic is the primary cause of the loss of control effectiveness. The control
efficiency decay functions can be used to derive the critical relationships
between average control efficiency and application frequency. Assuming, as
a first approximation, that control efficiency decays linearly from an
initial value of 100%, the average control efficiency for a given frequency
of application is the mean of 100% and the value at the end of the decay
cycle.
The quality rating of control performance data for a periodically ap-
plied control measure must address the reliability of the average control
efficiency for the particular application frequency tested. Obviously, a
spread in the measured values of instantaneous control efficiency is ex-
pected, as the efficiency decays. Rather the quality rating must be based
on how well the instantaneous values fit a decay function. At the time of
this writing, mathematically derived decay functions were available for
only a few of the control measures. Therefore, no quality ratings were
assigned to the control efficiency data presented.
Most of the studies identified in Tables 5-2 and 5-3 were performed on
roads in iron and steel plants or surface coal mines, using both Type 1 and
Type 2 study designs (as defined in Section 4.4). Because of differences in
the dust suppressants, application parameters and traffic conditions from
one study site to another, there is little overlap in the applicability of
the published control efficiency values.
In most of the extended tests of control performance, efficiency values
were found to decay with vehicle passes (and time) after application. In
Figures 5-2 through 5-4, the best-fit linear decay functions determined by
least-squares analysis are shown. In Figures 5-5 through 5-9, the data
points are connected by line segments.
64
-------
TABLE 5-2. SUMMARY OF MAJOR UNPAVED ROAD DUST SUPPRESSANT CONTROL EFFICIENCY TESTS
CT»
No. of
Dust valid
Ref. suppressant controlled Measurement
No. tested tests Test site method
1-3 Coherexid
Coherexe
Coherexg
5-6 Coherexg
7
10
a
b
Coherexg
Coherexg
Arco 2400
Lignosite
(50% solids)
Oustgard 11
Peladow
Trex (ammonium
lignin sul-
fonate)
2
4
5
4
2
91
91
73
(17)e
1
3
Steel plant
Steel plant
Steel plant
Steel plant
Steel plant
Public road
Public road
Public road
Public road
Surface coal
mine
Taconlte nine
P
P
P
P
P
U/0
U/D
U/0
U/0
P
P
P = profiling; U/0 = upwind/downwind.
TP = total paniculate;
TSP =
RP = respirable paniculate;
c
Particles of less than
aerodynamic diameter).
30 \im
total suspended paniculate;
FP = fine particulate
stokes diameter (47 \im
Time after
Application Dilution
intensity ratio
application (gal. sol.
(days) yd*)
< 7
1-2
1-2
Unknown
14-15
30-270
30-270
30-270
3-60
90
< 7
Unknown
0.19
0.19
Unknown .
Unknown
11.5%
\0.33f
3.5
1 0.125°
«0.25T
0.5
0.6
0.08
/ (gal
gal
1:
1:
1.
. chera:
. H20)
9
6
6
Unknown
1:
1:
1:
1:
1:
1:
1:
1:
1:
4-1:7
?'}
0
I?)
09
2
4
Four applications were put down with
2 weeks
e Initial
f Repeat
9 Not rtil
after fourth
application.
application.
uteri furt hap*
Avg.
vehicle Control b
weight efficiency
(ST) (%)
3
50
3
4-19
26
4
4
4
4
3
91C
TP
TSP
FP
TP
TSP
FP
TP
TP
TSP
RP
TSP
RP
TSP
RP
TSP
RP
TSP
RP
FP
92-98.
91-96
90-97
94-100
91-99
92-97
81
99
53
64
96
57
46
42
48
24
95
95
88
110-127 TSP 88
testing
beginning
application.
hnwjauA**
Hi 1 ii 1 \r
in AC cKi
innari nrt
fr
specified.
-------
01
01
TABLE 5-3. SUMMARY OF MAJOR UNPAVED ROAD DUST SUPPRESSANT CONTROL EFFICIENCY DECAY
FUNCTION TESTS
Kef
No.
1-3
4
8
a
b
c
Oust
No. of
valid
Application
Tine after Intensity
Dilution
ratio
suppressant controlled Heasurement application (gal. sol./ (gal. chen:
tested tests Test site nethod" (days) yd1) gal. H,0)
Petro Tac
Coherexfi)
CoherexB
Coherexe
Oil well brine
Arcole 220 and
Flanblnder
l.lquiDow
Soil Senent
Biocat
Flamblnder
Arco 2200
P = profiling; U/D =
Initial application.
a
B
4
5
5
5
a
18
8
12
12
3
4
16
a
16
4
Steel plant
Steel plant
Steel plant
Steel plant
Steel plant
Steel plant
Surface coal
nine 1
Surface coal
nine 2
Surface coal
nine 3
Surface coal
mine 1
Surface coal
mine 2
Surface coal
nine 3
Surface coal
nine 1
Surface coal
nine 2
Surface coal
vine 3
Surface coal
nine 2
Surface coal
nine 3
P
P
P
U/D
U/D
U/D
P
P
P
P
P
P
P
P
P
P
P
upw i nd/downw 1 nd .
2-116
7-41
4-35
17-35
17-35
17-35
14-49
7-28
14-21
21-42
7-35
7-14
14
7-28
7-21
7-28
7
0.70.
0.82%
1.5
3.8
1.9
0.27-0.6
0.27-0.6
0.3-0.6
1.9-3.0
1.0
2.0
0.5-2.1
0.5-2.0
1.8
0.9-2.8
1.1-2.3
1
1
1
1
N
1
1
1
1
i
1
I
1
1
1
1
1
*c.d
4
at
4
1.6
1.6
1.9
8.3
6.4
20.000
4.6
4.6
4.6
7
6.1
Ihe main test section of the road was
after the Initial application.
* Values
represent range of
haul truck
Avg. Efficiency
vehicle decay
weight
(sn
23-34
27-50
31-56
3
3
3
28-66*
44-83*
70-27*
A
22-89*
38-82*
n
70-276*
16-65*
51-69*
70-276*
18-80*
70-276*
retreated 44
weights from
function
(Fig.)
5-2
5-3
5-4
5-5
5-5
5-5
5-6
5-6
5-6
5-7
5-7
5-7
5-8
5-8
5-8
b-9
5-9
days
empty to
Bo-.oat ar^ilr^t Inn loaded vehicles. Haul truck has 10 wheels at nines 1 and 2
and six wheels at nine 3,
-------
Petro-Tac®
100
- ao
I so
a
«
i *
^ 20
Rating A
Awtetlon mtensrty
Dilution Rano 20%
Avg. van. wetgnt 27 Mg
Avg. No. of 'Wheels 9 2
Avg. AOT 414
IP
Vemeie "asses after Aooucanon
(lOCO's)
10
Vanicle Passes atler Aooneanon
(1000's)
Figure 5-2. Control efficiency decay for an initial application
of Petro Tac®1"3
67
-------
Cohere*9
Rating B
100
~ 80
I-
_o
ui
o
20
I I
Application Intensity 3.3//m2
Dilution Ratio 20%
Avg. Veh. Weight 34 Mg
Avg. No. of Wheels 6.2
Avg. AOT 95
TP
IP
100
80
£
>.
g 60
* 40
20
0
PM1Q
1234
Vehicle Passes after Application
(1000's)
1234
Vehicle Passes after Application
(1000's)
Figure 5-3. Control efficiency decay for an initial application
of Coherex®1"3
68
-------
Rating C
100
2 90
80
100
"
I
I
ao
Coherex®
Application Intensity
Dilution Ratio 1 7 gal. chem..gal. I
Avg. Ven. Weignt 39 Mg
Av$ NO. of Wheels 6.0
Avg. ACT 94
7P
lilt
PM
10
I I I I
0 12315
Venicie Passes after Application
J I
IP
I I II
FP
Venicie Passes after Aopncauon
(1000s)
Figure 5-4. Control efficiency decay for a reapplication
of Coherex®1"3
69
-------
Reapplicatfon of OWB (0.6 gal. sol./y
40
20
Application Intensity (gal. sol./yd2)
Dilution Ratio (gal. chem.:gal. H2O)
Avg. veh. Weight (tons)
Avg. NO. of Wheels
Ramblnder
4 Arcote
220
•
1.9
1:4
2
4
Oil
Welt
Brine
A
3.8
1:0
3
4
Coherex
•
1.5
1:4
3
4
12
18
24
Time after Application (days)
30
Figure 5-5. TSP control efficiency decay for light-duty
traffic on unpaved roads4
36
70
-------
LiquiDow*
ICO
8? 80
I 60
S
1 40
§5 20
0
Mine
Aooiieaflon intensity (gal. soi./yo2)
Dilution Ratio (gal. ciiem..gal. H^)
Avg. Vert. Weight (tons)
Avg. Na of Wheels
Rating
1
0.27-0 6
1:16
28-66
10
0
2
0.27-0.6
1-18
44-83
10
0
3
03-06
1 19
70-276
6
0
Toeical
Application
I I I I I
Mixed
Application
£
u
FP Conliol El
IUU
80
60
40
20
°,
Topical
_ Aooiicanon
- ts^r-—
!
\
) 5 10 15 20 25 3C
VeniclB Passes after ApoNcation
(1000's)
I
I
I
Mixed
Aooiicanon
I
I
5 10 15 20 25
Vehicle Passes after Aooiicanon
(IQOO'S)
30
Figure 5-6. Decay of control efficiency for LiquiDow®
applied to haul roads8
71
-------
# 80
ff
•S €0
ui
1 *
| 20
0
100
# 80
| 60
| 40
t 20
0
Mlm
Appticauon intensity (gal. souyo2)
Dilution Ratio (SSL cnem.:gaL HjO)
Avg, Van. Weight (tons)
Avg. No. ot Wheels
Rating
Topical
• Application
\ A
/•\
rt \T
" -y X\
1 1 *I 1 !"•
Soil Sement® BIocat-Enzyme3
1 2 3
1.9-10 1.0 2.0
1:8.3 1:3.4 1:20.000
22-89 38-62 70-278
10 10 6
330
Topical
— \«?
\**^»
3 S 10 IS 20 25
Mixed
_ Application
—
~\
«
•
l\ 1 1 1 1
Mixed
Application
-
•• •
-rf
1 1 1 1 1
30 0 S 10 15 20 25 2
Venicie Passes alttr Application
OOOO'S)
Vehicle Passes attar Application
OOOO's)
Figure 5-7. Decay of control efficiency for Soil Sement®
and Biocat-Enzyme® applied to haul roads8
72
-------
Rambinder®
Mint
Application intensity (gal. scUyd2)
Dilution Rano (gal. diem.. gal. HyO)
Avg. Veh. Weigtn (torn)
Avg. No. of Wheels
Rating
I
O.S-Z.1
T46
16-65
10
E
2
0.5-2.0
V4.6
51-69
10
C
3
1.8
T46
70-276
8
C
1
J
3
1
IUU
80
60
40
20
0
Topical
_ Application
_ ^j- Mine t
- ^^^
?
1 1 1 1 1
Mixed
Application
£
J
UJ
FP Cunliol
IUU
80
€0
40
20
0
Topical
_ Appiicaoon
—
X*
_ ^ Mine 1 ./
I ' 1 1 1
5 ;0 15 20 25
Venicie Passes atter Application
(1000's)
30
I
Mixeo
Acpheaticn
I
J_
5 10 13 20 £5 20
Vehicle Passes atter Aooiication
<1QOQ-SI
Figure 5-8. Decay of control efficiency for Flambinder®
applied to haul roads8
73
-------
Arco 2200®
100
ui
i
Topical
Application
Mine 3
J I
MlM
Application Intensity (gal. sol./ya.2)
Dilution Ratio (eal. chem.:oal. H^)
Avg. Van. Weight (tons)
Avg. NO. of Wheat*
Rating
2
0.9-2.8
1:7
18-80
10
C
3
11-2.3
1-6.1
70-276
S
E
•Mine 3
\
, X
Mixed
Application
100
a.
•j.
' Mine 3
Topical
Application
., Mine 3
\
Mixed
Application
10 15
20
25 30
10
15
20
25
30
vehicle Passes after Application
(1000's)
Vehicle Passes alter Application
(1000-3)
Figure 5-9. Decay of control efficiency for Arco 2200®
applied to haul roads8
74
-------
Apparent increases in control efficiency with vehicle passes were ob-
served in several test series from Reference 8. This anomalous behavior
is thought to be the result of moisture effects on the uncontrolled emission
rate, which was measured simultaneously with each controlled emission rate.
In other words the efficiency values were not always referenced to a dry
uncontrolled emission rate.
An empirical model for the performance of a watering as a control
technique has been developed.11 The supporting data base consists of
14 tests performed in four states during five different summer and fall
months.1"3 The model is:
C = 100 - °'8P d *
(5-2)
where:
C = average control efficiency (percent)
P = potential average hourly daytime evaporation rate (mm/hr)
d = average hourly daytime traffic rate (hr-1)
i = application intensity (L/m2)
t = time between applications (hr)
The data to support this empirically based mathematical model are shown in
Table 5-4. No significant difference in the average control efficiency of
TABLE 5-4. FIELD DATA ON WATERING CONTROL EFFICIENCY1-3
Location
N. Dakota
New Mexico
Ohio
Missouri
a
No. of
tests
4
5
3
2
Month
October
July/Aug.
November
September
Applic.
inters.
(L/raZ)
0.2
0.2
0.6
1.9
Avg. time
between
applic.
(hr)
1.3
2.0
4.5
2.3
Avg.
traf.
rate
(hr-i)
40
23
98
72
Avg.
poten.
evap.
(mm/hr)
0.084
0.23
0.042
0.26
Avg.
control
eff.a
(S)
59
69
77
88
No significant difference in control efficiency as a function of particle
size was observed.
75
-------
watering as a function of particle size has been established to date. As
with all empirical models, Eq. 5-2 should not be applied beyond the ranges
of independent variable values tested.
The control efficiencies afforded by paving of unpaved road segments
can be estimated by comparing the AP-42 emission factors for the unpaved
and paved road conditions. The emission factor for the paved road condition
requires an estimated silt loading on the paved surface. An urban street
dust loading model12 can be used to estimate silt loadings as a function of
traffic volume. The model is expressed as follows:
sL = 21.3 (ADT)~°-41 (5-3)
where:
sL = silt loading (g/m2)
ADT = average daily traffic (vehicles/day)
This urban model was developed from silt loading measurements in five urban
areas (Baltimore, Buffalo, Granite City (IL), Kansas City, and St. Louis).
All of the streets were paved edge to edge and had curbs and gutters. The
calculated control efficiencies for paving are usually of the order of 90%.
The results of additional field testing of haul road watering are pre-
sented in Table 5-5.
5.2 IMPROVEMENT OF PAVED TRAVEL SURFACES
5.2.1 Design Considerations
Resuspended dust emissions from vehicles traveling on paved roads can
be controlled by removing the dust from the road surface. Techniques for
removing dust from paved roads include broom sweeping, vacuum sweeping,
flushing, and a combination of flushing and broom sweeping. The control
efficiency afforded by any of these road cleaning techniques decays with
time and with vehicle passes after cleaning. This is due to the buildup of
dust on the surface because of track-on from unpaved surfaces, release of
vehicle underbody catch debris, atmospheric deposition, and rainstorm wash-
on.
76
-------
TABLE 5-5. COMPOSITE CONTROL EFFECTIVENESS
OF WATERING8
Period between
applications (min)
120
Mine 1
Control eff. (%)
TSP 16
FP 29
Vehicles/hr 32
Mine 2
Control eff. (%)
TSP
FP
Vehicles/hr
60
37
40
24
41
26
65
30
51
43
28
59
47
78
The control efficiency achieved by vacuuming is influenced by many
variables such as:
1. Blower capacity in ACFM.
2. The air velocity generated along the road surface.
3. The condition of the road surface (small particles can be shielded
from capture if they rest in holes characteristic of a rough, poor
quality surface).
4. Characteristics of the gutter broom (e.g., rpm, type of bristle,
number of bristles per unit area).
5. Type of device used to remove particles (e.g., bags, water sprays,
scrubbers, etc.).
77
-------
5.2.2 Performance Data
In contrast to controls for unpaved roads, few published values are
available for control measures applicable to paved roads. A limited number
of exposure profiling tests have been performed to measure the control
efficiency achieved by vacuum sweeping, water flushing, and water flushing
followed by broom sweeping of steel plant paved roads.1 Also, the efficiency
of an improved vacuum sweeper has been determined indirectly by quantifying
the reduction in surface loading on two city streets.13
Tables 5-6 and 5-7 list the available control efficiency data for each
of the four road cleaning techniques mentioned above. In Table 5-6, the
control efficiencies of vacuuming are listed as single values measured at
specific times after application. In Table 5-7, the control efficiencies
of the remaining techniques are quantified as a function of vehicle passes
after application. All the data in Tables 5-6 and 5-7 are based on field
testing using the exposure profiling method.
The broom sweeper control efficiency data from Table 5-7 indicate that
the highest control efficiency achievable by broom sweeping alone is 27%
immediately after application. The data suggest that daily broom sweeping
would achieve approximately 25% control. The principles behind the effec-
tiveness of broom sweeping suggest that broom sweeping alone cannot be im-
proved enough to capture an adequate amount of fine particulate.
The flusher control efficiency data suggest that flushing at a rate of
0.48 gal/yard2 can produce a maximum of 69% control immediately after appli-
cation and that it will decay to zero after 300 vehicle passes. The equa-
tion presented in Table 5-7 was based on tests conducted at a steel plant in
Houston, Texas. The average vehicle weight during testing was 10 tons, and
the road was completely surrounded by unpaved areas accessible to vehicles.
The control efficiency equation in Table 5-7 shows that water flushing and
broom sweeping together are more effective than either technique used
separately.
Emissions of traffic-entrained road dust can also be reduced by resur-
facing of paved roads that have deteriorated resulting in increased surface
dust loadings. The control efficiency resulting from resurfacing of a paved
78
-------
TABLE 5-6. MEASURED SINGLE-VALUED PARTICULATE CONTROL
EFFICIENCIES FOR VACUUM SWEEPING1
Vacuum type
Once-through
Blower
capacity
(cfm)
12,000
Time after
application
(hr)
2.8
24
2.1
4.1
Instantaneous
control
efficiency
TP IP
70 51
52 58
48 16
16 0
As measured to the midpoint of the test.
TABLE 5-7. PARTICULATE CONTROL EFFICIENCY DECAY FUNCTIONS
FOR BROOM SWEEPING AND FLUSHING1
Average
vehicle
Application weight
Control intensity (tons)
Water flushing 0.48 gal /yd2 10
Water flushing 0.48 gal/yd2 13
followed by
broom sweeping
Broom sweeping - 12
Instantaneous control
efficiency decay function3
TP IP
66 - 0.130 V 69 - 0.231 V
90 - 0.294 V 96 - 0.263 V
24 - 0.164 V 27 - 0.032 V
Equation yields control efficiency in percent; V = number of vehicle
passes after control is employed.
Control efficiency decay function obtained by difference.
79
-------
road (application of 2 in. of hot-mix asphalt) may be estimated as equal to
the anticipated percentage reduction in silt loading on the travel lanes.
This is based on the proportional relationship between emissions and silt
loading in the AP-42 emission factor for industrial paved roads.
Curbs are effective in keeping vehicles on the pavement, thereby elim-
inating tracking from the edge of the pavement. IJowever, other techniques
such as painting the road 1 to 2 ft from the edge with a stripe and instal-
ling parking caution signs may accomplish this objective at far less expense.
Little additional control efficiency is gained by installation of continu-
ous curbing with gutters and sewers unless all adjacent areas (e.g., parking
lots and driveways) are also paved. In effect curbs would reduce loadings
to that of the urban model (Equation 5-3).
5.3 STABILIZATION OF PILES/EXPOSED AREAS
5.3.1 Design Considerations
Wind erosion of open storage piles and exposed areas is a recognized
source of particulate air pollution associated with the mining and process-
ing of metallic and nonmetallic minerals. Preventive methods for control
of windblown emissions from raw material storage piles consist of wetting,
chemical stabilization, and enclosures. Physical stabilization by covering
the exposed surface with less erodible aggregate material and/or vegetative
stabilization are seldom practical control methods for raw material storage
piles.
5.3.2 Performance Data
To test the effectiveness of controls for wind erosion of storage piles
and tailings piles, wind tunnel measurements have been performed. Although
most of this work has been carried out in laboratory wind tunnels, portable
wind tunnels have been used in the field on storage piles1 and tailings
piles.14 Laboratory wind tunnels have also been used with physical models
to measure the effectiveness of wind screens in reducing surface wind velo-
city.
80
-------
A portable wind tunnel has been used to measure the control of coal
pile wind erosion emissions by a 17% solution of Coherex® In water applied
at an intensity of 3.4 L/m2 (0.74 gal/yard2), and a 2.8% solution of Dow
Chemical M-167 Latex Binder in water applied at an average intensity of 6.8
L/m2 (1.5 gal/yard2).1 The control efficiency of Coherex® applied at the
above intensity to an undisturbed steam coal surface approximately 60 days
before the test, under a wind of 15.0 m/s (33.8 mph) at 15.2 cm (6 in.)
above the ground, was 89.6% for TP and approximately 62% for IP and FP.
The control efficiency of the latex binder on a low volatility coking coal
is shown in Figure 5-10.
5.4 ENCLOSURES
As described in Section 4, enclosures are an effective means by which
to control fugitive particulate emissions from open dust sources. Enclo-
sures can either fully or partially enclose the source. Full enclosures
are also capable of either being evacuated through some type of dust col-
lector (active) or nonevacuated (passive) as the case may be. Included in
the category of partial enclosures are porous wind screens or barriers.
This particular type of enclosure is discussed in detail below.
5.4.1 Design Considerations
With the exception of wind fences/barriers, a review of available
literature reveals no quantitative information on the effectiveness of
enclosures to control fugitive dust emissions from open sources. Types of
passive enclosures traditionally used for open dust control include three-
sided bunkers for the storage of bulk materials, storage silos for various
types of aggregate material (in lieu of open piles), open-ended buildings,
and similar structures. Practically any means that reduces wind entrainment
of particles produced either through erosion of a dust-producing surface
(e.g., storage silos) or by dispersion of a dust plume generated directly
by a source (e.g., front-end loader in a three-sided enclosure) is generally
effective in controlling fugitive particulate emissions. However, available
data are not sufficient to quantify emission reductions.
81
-------
100
80
o
UJ
o
o
O
60
40
20
6.8 ^/m2(l.5gal/yd2)of
2.8% Solution in Water
Tunnel Wind
Speed = 17 m/s (38 mph)
at 15 cm (6.0 in)
Above the Test Surface
Key:
l
Figure 5-10.
234
Time After Application (Days)
Decay in control efficiency of latex binder
applied to coal storage piles1
Partial enclosures used for reducing windblown dust from large exposed
areas and storage piles include porous wind fences and similar types of
physical barriers (e.g., trees). The principle of the wind fence/ barrier
is to provide an area of reduced wind velocity which allows settling of the
large particles (which cause saltation) and reduces the particle flux from
the exposed surface on the leeward side of the fence/barrier.
Wind fence/barriers can either be man-made structures or vegetative in
nature. One type of screen material, made out of a textile fabric, has been
used effectively first in Europe and then in the United States.15 Wind
breaks consisting of tree lines and other types of vegetation have also been
used to shelter large open areas.16
82
-------
5.4.2 Performance Data
A number of studies have attempted to determine the effectiveness of
wind fences/barriers for the control of windblown dust under field condi-
tions. Several of these studies have shown both a significant decrease in
wind velocity as well as an increase in sand dune growth on the lee side of
the fence.16'17'18-19 The degree of emissions reduction varied from study
to study ranging from 0 to a maximum of about 90% depending on test condi-
tions.18-20 A summary of available test data contained in the literature
on the control achieved by wind fences/barriers is provided in Table 5-8.
Various problems have been noted with the sampling methodology used in
each of the studies conducted to date. These problems tend to limit an
accurate assessment of the overall degree of control achievable by wind
fences/barriers for large open sources. Most of this work has either not
thoroughly characterized the velocity profile behind the fence/barrier or
adequately assessed the particle flux from the exposed surface.
5.5 WET SUPPRESSION SYSTEMS
Fugitive emissions from aggregate materials handling systems are fre-
quently controlled by wet suppression systems. These systems use liquid -
sprays or foam to suppress the formation of airborne dust. The primary
control mechanisms are those that prevent emissions through agglomerate
formation by combining small dust particles with larger aggregate or with
liquid droplets. The key factors that affect the degree of agglomeration
and, hence, the performance of the system, are the coverage of the material
by the liquid and the ability of the liquid to "wet" small particles. This
section addresses two types of wet suppression systems—liquid sprays which
use water or water/surfactant mixtures as the wetting agent and systems
which supply foams as the wetting agent.
5.5.1 Basic Design Considerations
Liquid spray wet suppression systems can be used to control dust emis-
sions from materials handling at conveyor transfer points. The wetting
agent can be water or a combination of water and a chemical surfactant.
83
-------
TABLE 5-8. SUMMARY OF AVAILABLE CONTROL EFFICIENCY DATA
FOR WIND FENCES/BARRIERS
Material or control parameter
Reference No. 18
Reference No. 20
ly|ie ot fence/harrier
Poro<y uf fence/barrier
Height/length of fence/barrier
Type of erodable material
Material characteristics
Incident wind speed
Lee-side wind speed
Paniculate measurement technique*
Test data rating
Measured participate control0
efficiency
Textile fabric
&OX
1.8 a/50 n
Flyasli
XII20 =1.6
X<58 (in = 14.7
X<45 Mm = 4.6
Average (no screen) =4.3 n/s
(9.7 mph)
Average (upwind) = 5.32 n/s
(11.9 mph)
Average - 2 m/s (4.0 mph)
or 64% reduction
U/0 - Hi-vol and Ill-wol
w/SSI (11 tests)
TP = 64X (average)
ISP = OX (average)
Wooden cyclone fence
50X
J u/12 n
Mixture of topsofl and coal
Unknown
Maximum = 27 n/s (60 nph)
Unknown
U/U - Bagnold catchers
(1 test)
IP = aSX (average)
U/D = Upwind/downwind sampling. D
Ili-Vol = High volume air sampler; Hi-vol w/SSI =
High volume air sampler with 15 |imA
size-selective inlet (SSI)
TP = Totdl partitulate matter
ISP = Total suspended particulate odller (particles < - 30
Data rated using criteria specified
in Section 4.4.
-------
This surfactant, or surface active agent, reduces the surface tension of
the water. As a result, the quantity of liquid needed to achieve good con-
trol is reduced. For systems using water only, addition of surfactant can
reduce the quantity of water necessary to achieve a good control by a ratio
of 4:1 or more.21-22
The design specifications for wet suppression systems are generally
based on the experience of the design engineer rather than on established
design equations or handbook calculations. Some general design guidelines
that have been reported in the literature as successful are listed below:
1. A variety of nozzle types have been used on wet suppression sys-
tems, but recent data suggest that hollow cone nozzles produce
the greatest control while minimizing clogging.23
2. Optimal droplet size for surface impaction and fine particle
agglomeration is about 500 urn; finer droplets are affected by
drift and surface tension and appear to be less effective.24
3. Application of water sprays to the underside of a conveyor belt
improves the performance of wet suppression systems at belt-to-
belt transfer points.23
Micron-sized foam application is an alternative to water spray systems.
The primary advantage of foam systems is that they provide equivalent con-
trol at lower moisture addition rates than spray systems.25 However, the
foam system is more costly and requires the use of extra materials and equip-
ment. The foam system also achieves control primarily through the wetting
and agglomeration of fine particles. The following guidelines to achieve
good particle agglomeration have been suggested:26
1. The foam can be made to contact the particulate material by any
means. High velocity impact or other brute force means are not
required.
2. The foam should be distributed throughout the product material.
Inject the foam into free-fall ing material rather than cover the
product with foam.
3. The amount applied should allow all of the foam to dissipate.
The presence of foam with the product indicates that either too
much foam has been used or it has not been adequately dispersed
within the material.
85
-------
5.5.2 Performance Data
Available data for both water spray and foam wet suppression systems
are presented in Tables 5-9 and 5-10, respectively. The data primarily in-
cluded estimates of control efficiency based on concentrations of total
participate or respirable dust in the workplace atmosphere. Some data on
mass emissions reduction are also presented. The data should be viewed
with caution in that test data ratings are generally low and only minimal
data on process or control system parameters are presented.
The data in Tables 5-9 and 5-10 do indicate that a wide range of ef-
ficiencies can be obtained from wet suppression systems. For conveyor
transfer stations, liquid spray systems had efficiencies ranging from 42 to
75%, while foam systems had efficiencies ranging from 0 to 92%. The data
are not sufficient to develop relationships between control or process
parameters and control efficiencies. However, the following observations
relative to the data in Tables 5-9 and 5-10 are noteworthy:
1. The quantity of foam applied to a system does have an impact on
system performance. On grizzly transfer points, foam rates of
7.5 ft3 to 10.5 ft3 of foam per ton of sand produced increasing
control efficiencies ranging from 68 to 92%.27 Foam rates below
5 ft3 per ton produced no measurable control.
2. Material temperature has an impact on foam performance. At one
plant where sand was being transferred, control efficiencies
ranged from 20 to 65% when 120°F sand was handled. When sand
temperature was increased to 190°F, all control efficiencies were
below 10%.27
3. Data at one plant suggest that underside belt sprays increase con-
trol efficiencies for respirable dust (56 to 81%).2S
4. When spray systems and foam systems are used to apply equivalent
moisture concentrations, foam systems appear to provide greater
control.27 On a grizzly feed to a crusher, equivalent foam and
spray applications provided 68% and 46% control efficiency, re-
spectively.
5.6 PLUME AFTERTREATMENT
The injection of charged or uncharged water droplets into a dust plume
can be effective means by which to settle the suspended particles.
86
-------
TABLE 5-9. SUMMARY OF AVAILABLE CONTROL EFFICIENCY DATA FOR WATER SPRAYS
00
Refeience lyue ol Type ul
Nil process oaleridl
a
b
c
A Chain feeder Coal
to belt
transfer
Bell-to-belt Coal
transfer
27 Grljily Run or
transfer mill tdiiil
to bucket
elevator
28 Conveyor Coal
transport
anil
transfer
Piocess
desly.li/
opfernlliiu
parameters
3 ft ill up.
8 tons coal
per load
Not speLifled
Not sued I led
2 tie III 0 91
• and 1 07 i
widths,
- 500 a
length
Control system
paraaelei s
8 Sprays. 2 5 yj>o.
ahove liell only
B Sprays. 2 5 ypn »
1 spray on under-
Side of bill
8 Sprays. 2.5 Qpn-
above bell only
8 Spiays, 2 5 gpa »
1 spray on under-
side of belt"
Liquid vol. 757 ul
Liquid vol. 1,324 nL
llquld vol. 1.324 nl*
Liquid vol. 1.324 «t'
3 Spray bart/bell,
D underside or tail
pulley, 5-10 cc
11,0/sec per bar.
Delevan fcfanjel"
spiays
MAM samples are from Realtime Aerosol Monitors, light scattering
type instruments. Type 1 tests include measurements of a single
source with and without contrul
lesl rdllng scheme defined In Section 4.4
IP = lotal Part leiil die; HP - Repairable Pat t leulate
Measurement No of
technique tests
Personnel samplers, 10
Type 1 lesl scheme
Personnel samplers, 4
Type 1 lesl scheme
Personnel samplers, 10
Type 1 lesl scheme
Personnel sanpleis, 4
lype 1 lesl scheme
Personnel sampleis, NA
Type 1 lesl scheme
Personnel samplers. IIA
Type 1 lesl scheme
Personnel samplers. NA
Type 1 lesl schene
Personnel samplets, NA
Type 1 lesl schene
Personnel samplers. NA
Type 1 test scheme"
Control dpplled dl a poinl
upstream.
e Water « I.5X surfactant
' Water < 2. UK surfactant
Test Control
ddla K efficiency
i-allng" (X)
C RP be
TP 59
C DP 81
TP 87
C RP 53
C RP 42
C RP 46
C RP 58
C HP 54
C RP 54
D RP 65-75
rive tiansiers
Individual lesl values not specified, no
airflow ddla ur QA/QC data
-------
TABLE 5-10. SUMMARY OF AVAILABLE CONTROL EFFICIENCY DATA
FOR FOAM SUPPRESSION SYSTEMS
Reference
No.
z;
Type of
process
Bell-lo-taell
transfer
Belt-to-bin
transfer
Bulk loadoul
Screw- lo-
belt
transfer
Bucket ele-
vator dis-
charge
Belt-to-balt
transfer
Feeder bar
discharge
Crinley
lype or
•aterlal
10-nesh
glass sand
30-mesh
glass sand
JO-nesh
glass sand
Cleaned run-
of-nlne
sand
Cleaned run-
of-alne
sand
Cleaned run-
of-aine
sand
Cleaned run-
of-Blne
sand
Dried run of
Process
design/
operating
parameters
Sand temp.
- 1ZO°F
Sand leap.
- liO't
Sand leap.
- izo°r
174 tons/hr
Sand temp.
- 190"r
179 tons/hr
Sand leap.
- 190°F
193 tons/lir
Sand leap.
- 190"F
191 tons/hr
Sand tenp.
~ 190°F
Hot specified
Control systea
paraaelers
Hot specified
Not specified
Hot specified
Moisture <* O.ZS%
Moisture » 0.18X
Moisture = 0. 18X
Moisture = 0.19X
foam rate = 10. S ft*
Heasurenent No. of
technique" tests
Personnel samplers. NA
lype 1 test scheme
Personnel samplers, HA
lype 1 test scheae
Personnel saaplers. HA
Type 1 test schene
Grav/RAH staplers.* 4
Type 1 scheme
RAM/personnel 5
sanplers.
Type 1 test scheae
RAM/personnel 8
couplers.
Type 1 test scheae
RAM/personnel 6
samplers,
Type 1 lest scheae
Personnel saaplers. Z
Test
data .
rating"
C
c
C
c
c
c
c
c
Control
efficiency0
(X)
RP Z0d
RP 33d
RP 6Sd
RP 10d
RPBd
RP7d
RPZd
RP 92
•Ine sand
to bucket
elevator
/ton sand
Liquid rate = 0.3B
gal/Bin
Foaa rate = 8.2 ft>
/ton sand
Liquid rale = 0.34
gal/Bin
foam rate =7.5 fl>
/ton sand
Liquid rate = 0.20
gal/Bin
Type 1 test scheu
Personnel sanplers.
Type 1 test scheae
Personnel saaplers,
Type 1 lest scheae
RP 74
RP 68
RAH samples are froa Realline Aerosol Monitors, light scattering
lype Instruments. Type I tests Include neasureaents of a slnyle
source with and without control
lesl rating schene defined In Section 4 4.
RP = Resplrable Parllculate.
Efficiency based on concentrations only.
-------
TABLE 5-10. (concluded)
00
10
Reference Type of
No. process
25 Chain feeder
to bell
transfer
Belt-to-bell
transfer
27 Grizzley
Type of
material
Coal
Coal
Dried run-
of-mine
sand
Process
design/
operating
parameters
3- ft drop,
8 tons coal
per load
Not specified
Nol specified
Control system
parameters
50 psl H,0. 2.5%
reagent. 4 nozzles
15-20 elm foam
applied
50 psi H,0, 2.5%
reaycnt. 4 nozzles
15-20 cfm foam
applied
Foan rate = 4.8 ft1
/ton sand
Liquid rale = 0.18
Measuiemegl No. of
technique tests
Personnel samplers, 9
Type 1 test scheme
Personnel samplers, 9
Type 1 lest scheme
Personnel samplers. 2
Type 1 test scheme
Test
data .
ratimj
C
C
C
Control
efficiency11
<*)
RP 96
TP 92
RP 71
RP 0
gal/min
Foan rate =2.6 ft*
/ton sand
Liquid rate = 0.13
gal/ml ii
Liquid vol. 1,420 mL
Liquid vol. 1.300 ml
Liquid vol. 764 nL
Personnel samplers, 2 C RP 0
Type 1 test scheme
Personnel samplers, NA C RP 91
Type 1 lest scheme
Personnel samplers, NA C RP 73
Type 1 lest scheme
Personnel samplers. HA C RP 68
Type 1 lest scheme
RAH samples are from Realtime Aerosol Monitors, light scattering
type instruments. Type 1 tests include measurements of a single
source with and without control.
lest rating scheme defined in Section 4 4.
TP = Total Participate; RP = Respirable
Particulate.
Efficiency based on concentrations only.
Control applied at a point five transfers
iipslieam.
-------
In this section, available test data on plume after-treatment systems will be
provided as a guide to the environmental professional in the application of
such technology to the control of fugitive particulate emissions from open
sources.
5.6.1 Basic Design Considerations
A number of important parameters must be considered in the proper
application of plume aftertreatment using plain water. Since impaction is
the primary mechanism by which the water droplets capture suspended dust
particles, the size and velocity of the droplets injected into the plume
are critical to proper system design. According to the U.S. Bureau of
Mines (BOM), the optimum drop size for the capture of airborne respirable
dust (~ < 10 urn) is approximately 200 urn.29'30 The velocity of the droplets
injected into the dust plume should also be maximized to the greatest extent
possible.
Guidelines on the proper design and operation of water spray systems
have been published by the BOM.29'30 These guidelines include proper nozzle
selection, location of nozzles for optimum coverage of the dust plume, the
design of filtration systems to reduce nozzle wear and clogging. The reader
is referred to these documents for assistance in the application of plume
aftertreatment systems using plain water.
In the past several years, electrostatics has been used to augment
traditional water sprays for plume aftertreatment. Most mechanically
generated aerosol particles acquire a slight electrostatic charge.31 By
injecting a fog of oppositely charged water droplets into the plume, a
significant enhancement in the capture and removal process can be achieved
(especially for particles in the 1 to 2 \im size range.)32'33
Two companies currently market a commercial version of electrostatic
fogger. These units utilize induction charging and generally follow the
design originally developed by Hoenig.31 In addition to the commercial fog-
gers, an experimental unit (CFG) was developed under EPA sponsorship by a
California firm. This experimental model uses direct charging and a rotary
atomizer for the generation of charged fog.34
90
-------
The efficiency at which charged fog captures airborne particles depends
on several parameters: volumetric ratio (volume of spray to volume of dust
plume); contact time; droplet size; and charge-to-mass ratio (for water
droplets and dust particles). At present insufficient data are available
to quantify the relationships between these control parameters.
Since use of charged fog for the control of fugitive dust has been
tested only on a limited basis, relatively little data are available on
field performance. The application of charged fog has been suggested for
use in the crushed stone and smelting industries.35'36
5.6.2 Performance Data
Plume aftertreatment systems using plain water have been extensively
investigated in the laboratory by the U.S. Bureau of Mines.30'31'32'37'33
These studies have included an evaluation of both water sprays and steam
for the control of respirable particles. Most of this work was conducted
in a wind tunnel with dust concentrations measured by wet impingers up-
stream and downstream of the spray injection point. BOM research has indi-
cated a general reduction in respirable dust concentrations in the range of
20-60% using water sprays alone with an additional 14% increase in effi-
ciency when steam and water sprays are used concurrently.31'37 When sur-
factants were added to the water prior to atomization, a 10-15% increase
in efficiency was achieved in the capture of airborne respirable dust as
compared to water alone.39
A number of laboratory studies have also been conducted on the use of
charged water droplets (fog) for plume aftertreatment. Wind tunnel (or
chamber) studies have been performed by Hoenig, Kinsey, and McCoy under the
sponsorship of either the EPA or BOM.32'33'40'41 Reductions in dust con-
centration achieved by charged fog vary significantly from study to study,
depending on test conditions, type of dust and particle size. Generally, a
40-80% reduction in dust concentration seems to be typical over most particle
size ranges and test conditions. A significant enhancement in dust capture
efficiency was determined in the various studies for particles in the smaller
size ranges (i.e., < 1-2 umA) due to the electrostatic forces which act on
these size particles.
91
-------
In addition to wind tunnel OP chamber experiments, a number of investi-
gators have also-conducted field studies to measure the effectiveness of
charged fog to control fugitive dust. Hoem'g conducted some field investi-
gations as part of his original work with subsequent programs conducted by
Mathai, McCoy, and Brookman.31'33'39'41
As expected, control efficiencies determined in field tests are gene-
rally lower than those measured in the laboratory. Because all of the field
tests suffer from one or more deficiencies in experimental technique, data
quality is limited. Table 5-11 summarizes the available control efficiency
data for plume aftertreatment systems.
5.7 OTHER OPEN SOURCE CONTROLS
There are a number of open source control techniques which have not as
yet been evaluated on a quantitative basis, and thus no substantive test data
are available for control efficiency. These methods include: physical sta-
bilization of unpaved surfaces; mud/dirt carryout control for construction and
demolition; and modified tilling practices for agricultural operations. To
assist the environmental professional in the use of these techniques, Table
5-12 presents literature references which describe these methods in further
detail. The reader is directed to these references for guidance in the ap-
plication of these methods for open source control.
92
-------
TABLE 5-11. SUMMARY OF AVAILABLE CONTROL EFFICIENCY DATA FOR PLUME
AFTERTREATMENT SYSTEMS (OPEN DUST SOURCES)3
Ref
No. ly|>e ol process
lype Of
material
Fimess design/ .
operating paramuteis fogqer system
Measurement
technique
Number ,
of lesls"
lesl
data
raliny6
Average
cunliol .
efficiency
31 Belt conveyor" Quairy stone Hoi spec It led
Belt conveyor
Drup box
Capper ron-
cenlrate
Copper con-
cent i ate
Boxcar unloading Si Ilia sand
to
to
33
Front loader dump
into partially
enclosed hopper
BcntOfllle ore
BX < J7 tim
Nut specUleil
Not specified
Not spec 11 led
3-slded enclosure
10 dumps/25 aln
enclosuie volume
~ 40 B>
?-Ransbmg RCA foqnors
al 1811° finn each oilier
along direction ol belt
tiavel.
WIR - 94 6 cc/nln total
Ar = S / niVhr total
1-Ransbmq REA fogger
mounted above bell
discharyp,
WfR = 30-60 LC/oln
AT = not >|>eciMed
|-R«iisl»nq REA fogger
In diou box enclosure,
WrR = Not specified
AF = Not spec 1 1 led
4-Raiisluuq REA lugyers
located 90° apart around
source;
VfR = 30 cc/nln/fogyer
AF = Not
1-AeioVlronnenl CfC
mounleil at end of en-
closure,
WFR = 60 I/hi
AF = Hot specified
Near bell. 7-slage
Amlei son cascade
Impaclor
Near bell. CCA model
RUH-lul w/cyclono
Inside drup box
CCA model RDM 101
w/cyclone
Inside boxcar. HSA
personnel sanpler
Single pf Ili-vol
w/cyclone and
2-stage
IB
C <• 9 |W A = 70X
0 IP = S3-/ZX
RP = 64-77X
c RP = 65 n
0 HP = 8«
< 7.3 uoA - 44 5%
< 1 B (IDA = 48. IX
39
a
b
Belt conveyor Cnislied ure Conveyor wlrtlh = 1 5 n 6-Keyslone Dynamics Hoilel
Belt speed - 152 m/nin 109s located 1 5 m
Ventilation rale = above hell (spray con-
1&-61 B/QIII LIII rrnl w/dlrecllon of
bell oovemenl),
UTR = 300 cc/nln/fogger
AF = supply pressuie =
344 kPa
Includes only results of Meld testing
The Ransbuiy, Ritten, and Keystone foggers are based on the origins 1 Itoenly dnsiqn which
uses induction cliaiglmi and conuerclal spray no«les Ihc AeroVlrnnaent prototype units
use a lolary alumtter.and Uiiecl chaiging to produce cliaiged log AeroVlroiuncnt CFG =
200 im drops. 1 2(10) " C/u f 4 kV. J6-!*|A .
foyyei(s).
C/g <
walei (low ralp; AF ~ alrdow to
MSA peisoiuu-l sampler = 10 nig nylnn cyclone followed by a 37-nm (liter casselle
in can nylcin rye lone also used en CCA ftodel HDH-101 and RAH-1 cnnfiiicciius fiisliuueiits
U/0 = measui cuvnts taken upstiean ami downslieam ol I lie puinL wlieie chained lay Is
injected Into canveyoi tunnel Ili-vol = sldndaid lni|li volume all samplur. Ili-vol
w/SSI = hiijb vulime air s.implcr ei|iii|p(ied willi Siena 15 pnA siie-seld live inlet,
Ili-vol w/cyLlune ami ioi|iaLtui = hlijli volume air saupler ci|uip|iud with Siena Hoilel
230CI' LXLlcme precollet.t
-------
TABLE 5-11. (concluded)3
Ref.
No.
41
lype of process
Dump Into prlnary
crusher (lesl
Mo. 1)°
Bell-lo-bell
transfer (open)
(lest No. 6)
Crusher conveyor
(test No. 7)
lype of
nalerlal
Quarry rock
(basalt)
Sinter fines
Crushed line-
stone
(< 10 en)
Process design/
operating paraaelers
45 Hg/ truck load
Unloading tine =
30-60 sec
Pit volume = 192 a>
Drop height = l.Z a
Conveyor tunnel =
3 • dla.
rogger syslea
Z-Rlllen Fogger IVs at
90° Iron each other (one
upwind/one downwind):
WFR = 51-18 l/lir/fogyer
Af = 1.4-4.8 aVhr/fogger
Z- HI lien logger IVs
2-AoroVlronneiil CFCs lo-
cated 180* froe each
Irani for point;
WFR = 56.8 L/hr/fogger
AF = 3 fl nVhr/Rltten
rogger; SOX tax. (AV)
1-Rltlen logijer IV
2-AeroVI raiment CfGs
spray injected fnto tun-
Heasureaent Hunter .
technique17 of tests"
(32) Downwind: Ill-vul; 32
Hl-vol w/SSI;
Hl-vol w/4-llaue
Impactor
Above and next to 100
source: Hl-vol;
Hl-vol u/SSI; Hl-
vol w/cyclones and
4-stage inpactor
Above and next to 134
source: Hl-vol;
Hl-vol w/SSI; III-
Tesl
data
rating'
C
C
C
Average
control .
efficiency'
ISP - 57-5BX
IP = 46-53%
< - C unA =
31-55%
< 2-3 |WA =
0-93%
(all foggers)
ISP = 13-35%
IP = 0-28%
< 6 aA = 2-10%
nel counter-current to
direction of belt move-
nent;
VfR - 113.S l/hr (Kitten);
56.8 L/hr/AV foggrr
AF = 113.5 L/hr (Rltten);
50% aax. (AV)
vol w/cyclone and ,
4-stage lopactor"*
< 2-3 |inA = 31-50%
(all faggers)
Includes only results of field testing
The Ransburg, Rltten, and Keystone foggers are based on the original lloenlg design which
uses induction charging and comerclal spray nozzles. Ihe AeroVironaent prototype units
use a rotary atomizer and direct charging to produce chdrged fog. AeroVironaent CFG =
200 |» drops, 1.2(10)'* C/g 6 4 kV; 16-24 »' spray volume. Kitten Fngger IV = - 60 u»
drops e 75 L/hr; 0.11(10) • C/g e 12.5 kV. WFR = water flow rate; AF = airflow to
fogger(s).
HSA personnel sanpler • 10 on nylon cyclone followed by a 37-on filter cassette.
10 mo nylon cyclone also used on CCA Model BOH-101 and RAH-1 continuous Instruments.
U/D = measurements taken upttreaa and downstrean of the point where charged fofl is
Injected into conveyor tunnel. Hl-vol = standard high volume air sanpler; Hl-vol
w/SSI = high volme air sanpler equipped with Sierra IS uaA sfie-seleclive Inlet;
Hl-vol w/cyclone and Inpactor » high volume air sampler equipped with Sierra Model
230CP cyclone precollector and Sierra Model 230 slotted cascade impactor.
Data rated using criteria specified in Section 4.4.
IP = lotal Paniculate; RP = Resplrable Participate;
ISP = Total Suspended Partlculate; IP - Inhalable
Partlculate Include average efficiency for both
positively/negatively charged fog.
Truck dump into crusher pit.
Ho background samples collected during test program.
Samplers located both In tunnel next to conveyor and
above tunnel exit
Total number of uncontrolled and controlled tests conducted
-------
TABLE 5-12. LITERATURE REFERENCES FOR OPEN SOURCE CONTROLS WHERE
NO TEST DATA ARE AVAILABLE
Control method Literature reference(s)a
Physical stabilization 15, 42, 43
Vegetative stabilization 15, 16, 44
Mud/dirt carryout for construction 45
and demolition
Agricultural tilling 46, 47, 48
a Refers to list of references at the end of Section 5.
REFERENCES FOR SECTION 5
1. Cuscino, T., Jr., G. E. Muleski, and C. Cowherd, Jr. Iron and Steel
Plant Open Source Fugitive Emission Control Evaluation. EPA-600/2-83-
110, NTIS No. PB84-110568, U.S. Environmental Protection Agency,
Research Triangle Park, NC, October 1983.
2. Muleski, G. E., T. Cuscino, Jr., and C. Cowherd, Jr. Extended Evalua-
tion of Unpaved Road Dust Suppressants in the Iron and Steel Industry.
EPA-600/2-84-027, NTIS No. PB84-154350, U.S. Environmental Protection
Agency, Research Triangle Park, NC, February 1984.
3. Cowherd, C., Jr., R. Bohn, and T. Cuscino, Jr. Iron and Steel Plant
Open Source Fugitive Emission Evaluation. EPA-600/2-79-103, NTIS No.
PB299385, U.S. Environmental Protection Agency, Research Triangle Park,
NC, May 1979.
4. Russell, David, and S. Charles Caruso. A Study of Cost-Effective
Chemical Dust Suppressants for Use on Unpaved Roads in the Iron and
Steel Industry. American Iron and Steel Institute, December 1982.
5. Energy Impact Associates. An Alternative Emission Reduction Option
for Shenango Incorporated Coke and Iron Works, January 1981.
6. Roffman, A., et al. A Study of Controlling Fugitive Dust Emissions
from Nontraditional Sources at the United States Steel Corporation
Facilities in Allegheny County, Pennsylvania. Report prepared for
U.S. Steel Corporation, Pittsburgh, PA, December 1981.
95
-------
7. Schanche, Gary W., Martin J. Savoie, Jack E. Davis, Veda Scarpetta, and
Patricia Weggel. Unpaved Road Dust Control Study (Ft. Carson, CO).
Draft Final Report for U.S. Array Construction Engineering Research
Laboratory, Champaign, IL, October 1981.
8. Rosbury, Keith D., and Robert A. Zimmer. Cost-Effectiveness of Dust
Controls Used on Unpaved Haul Roads - Volume 1 of 2. Draft Final
Report, U.S. Bureau of Mines, Minneapolis, MM, December 1983.
9. Axetell, Kenneth J., and Chatten Cowherd, Jr. Improved Emission Fac-
tors for Fugitive Dust from Western Surface Coal Mining Sources -
Volumes I and II. EPA-600/7-84-048, U.S. Environmental Protection
Agency, Cincinnati, OH, March 1984.
10. Cuscino, Thomas, Jr. Taconite Mining Fugitive Emissions Study.
Minnesota Pollution Control Agency, Roseville, MN, June 1979.
11. Letter to Laxmi Kesari, U.S. Environmental Protection Agency, Washington,
D.C., from Chatten Cowherd, MRI, regarding control efficiency achievable
by watering, October 21, 1982.
12. Cowherd, C., Jr., and P. J. Englehart. Paved Road Particulate Emissions;
Source Category Report. EPA-600/7-84-077, NTIS No. PB84-223734, U.S.
Environmental Protection Agency, Research Triangle Park, NC, July 1984.
13. Calvert, Seymour, et al. Improved Street Sweepers for Controlling
Urban Inhalable Particulate Matter. EPA-600/7-84-021, NTIS No. PB84-
169622, U.S. Environmental Protection Agency, Research Triangle Park,
NC, February 1984.
14. Bohn, Russell R., and Jeffrey D. Johnson. Dust Control on Active Tail-
ings Ponds. Contract No. J0218024, U.S. Bureau of Mines, Minneapolis,
MN, February 1983.
15. Kinsey, J.S., et al. A Review of Traditional and Nontraditional Tech-
niques for the Control of Fugitive Particulate Emissions. Paper
No. 80-20.4, 73rd Annual Meeting of the Air Pollution Control Associa-
tion, Montreal, Quebec, June 22-27, 1980.
16. Chepil, N. S., and N. P. Woodruff, "The Physics of Wind Erosion and
Its Control," in Advances in Agronomy, Vol. 15, Academic Press, NY,
1963.
17. Carries, 0., and D. C. Drehmel. The Control of Fugitive Emissions Using
Windscreens. In: Third Symposium on the Transfer and Utilization of
Particulate Control Technology (March 1981), Volume IV, EPA-600/9-82-
005d, NTIS No. PB83-149617. April 1982.
18. Larson, A. G. Evaluation of Field Test Results on Wind Screen Effi-
ciency. Fifth EPA Symposium on Fugitive Emissions: Measurement and
Control, Charleston, SC, May 3-5, 1982.
96
-------
19. Westec Services, Inc. Results .of Test Plot Studies at Owens Dry Lake,
Inyo County, California. San Diego, CA, March 1984.
20. Radkey, R. L., and P. B. MacCready. A Study of the Use of Porous Wind
Fences to Reduce Particulate Emissions at the Mohave Generating Sta-
tion. AV-R-9563, AeroVironment, Inc., Pasadena, CA, 1980.
21. U.S. Environmental Protection Agency. Non-Metallic Mineral Processing
Plants, Background Information for Proposed Standards. EPA-450/3-83-
OOla, NTIS No. PB83-258103, Research Triangle Park, NC, March 1983.
22. JACA Corporation. Control of Air Emissions from Process Operations in
the Rock Crushing Industry. EPA-340/1-79-002, U.S. Environmental Pro-
tection Agency, Washington, D.C., p. 15, January 1979.
23. U.S. Bureau of Mines. Dust Knockdown Performance of Water Spray Noz-
zles. Technology News. No. 150, July 1982.
24. Courtney, W., and L. Cheng. Control of Respirable Dust by Improved
Water Sprays. Published in Respirable Dust Control Proceedings, Bureau
of Mines Technology Transfer Seminars, Bureau of Mines Information Cir-
cular 8753, p. 96, 1978.
25. Seibel, R. Dust Control at a Conveyor Transfer Point Using Foam and
Water Sprays. Bureau of Mines, Technical Progress Report 97, May 1975.
25. Cole, H. Microfoam for the Control of Source and Fugitive Dust Emis-
sions. Paper 81-55.2. Presented at the 74th Annual Meeting of the Air
Pollution Control Association, Philadelphia, PA, June 1981.
27. Volkwein, J. C., A. B. Cecala, and E. D. Thimons. Use of Foam for Dust
Control in Minerals Processing. Bureau of Mines RI 8808. 1983.
28. Ford, V. F. W. Bottom Belt Sprays as a Method of Dust Control on Con-
veyors. Mining Technology. September 1971.
29. Kost, J. A., et al. Guidebook for Dust Control in Underground Mining.
OFR 145-82, U.S. Bureau of Mines, Washington, D.C., December 1981.
30. Mukherjee, Sandip K., and Madan M. Singh. Design Guidelines for Im-
proved Water Spray Systems - A Manual. Contract No. J0308017, U.S.
Bureau of Mines, Washington, D.C., December 1981.
31. Hoenig, S. A. Use of Electrostatically Charged Fog for Control of
Fugitive Dust Emissions. EPA-600/7-77-131, NTIS No. PB276645, U.S.
Environmental Protection Agency, Research Triangle Park, NC, November
97
-------
32. Kinsey, J. S., et al. A New Concept for the Control of Urban Inhalable
Particulates by the Use of Electrostatically Charged Fog. In: Pro-
ceedings Fourth Symposium on Fugitive Emissions: Measurement and Con-
trol, EPA-600/9-80-041, NTIS No. PB81-174393, U.S. Environmental Pro-
tection Agency, Research Triangle Park, NC, December 1980.
33. Mathai, C. V. A New Charged Fog Generator for Inhalable Particle
Control. EPA-600/7-84-016, NTIS No. PB84-159284, U.S. Environmental
Protection Agency, Research Triangle Park, NC, April 1984.
34. JACA Corporation. Control of Air Emissions from Process Operations in
the Rock Crushing Industry. EPA-340/1-79-002, U.S. Environmental Pro-
tection Agency, Washington, D.C., January 1979.
35. Daugherty, D. P. and 0. W. Coy. Assessment of the Use of Fugitive
Emission Control Devices. EPA-600/7-79-045, NTIS No. PB292748, U.S.
Environmental Protection Agency, Research Triangle Park, NC, February
1979.
36. Cheng, L. and J. E. Emmerling. Collection of Airborne Coal Dust by
Steam. RI 7819, U.S. Bureau of Mines, Pittsburgh, PA, 1974.
37. Tomb, T. F. et al. Suppression and Collection of Respirable Coal Dust
Using Water and Stream. Ann. NY Acad. Sci., Vol. 200:724-736, December
1972.
38. Courtney, W. G. and L. Cheng. Control of Respirable Dust by Improved
Water Sprays. 1C 8753, U.S. Bureau of Mines, Pittsburgh, PA, 1977.
39. McCoy, J., et al. Evaluation of Charged Water'Sprays for Dust Con-
trol. Contract No. H0212012, U.S. Bureau of Mines, Minneapolis, MN,
January 1983.
40. Hoenig, S. A. Fugitive and Fine Particle Control Using Electrostati-
cally Charged Fog. EPA-600/7-79-078, NTIS No. PB298069, U.S. Environ-
mental Protection Agency, Research Triangle Park, NC, March 1979.
41. Brookman, E. T. and K. J. Kelley. Demonstration of the Use of Charged
Fog in Controlling Fugitive Dust from Large-Scale Industrial Sources.
EPA-600/2-83-044, NTIS No. PB83-217828, U.S. Environmental Protection
Agency, Research Triangle Park, NC, June 1983.
42. Bonn, R., et al. Dust Control for Haul Roads. Contract No. J0285015,
U.S. Bureau of Mines, Washington, O.C., February 1981.
43. Albrecht, S. C., and E. R. Thompson. Impact of Surface Mining on Soil
Compaction in the Midwestern U.S.A. Contract J0208016, U.S. Bureau of
Mines, Minneapolis, MN, February 1982.
44. Donovan, R. P., et al. Vegetative Stabilization of Mineral Waste
Heaps. EPA-600/2-76-087, NTIS No. PB252176, U.S. Environmental Pro-
tection Agency, Research Triangle Park, NC, April 1976.
98
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45. Englehart, P., and J. Kinsey. Study of Construction Related Mud/Dirt
Carryout. EPA Contract No. 68-02-3177, Work Assignment 21, U.S. En-
vironmental Protection Agency, Region V, Chicago, IL, July 1983.
46. Agriculture Research Service. How to Control Wind Erosion. Agricul-
ture Information Bulletin No. 354, U.S. Department of Agriculture,
Washington, D.C., June 1972.
47. Hayes, W. A. Mulch Tillage in Modern Farming. Leaflet No. 554, U.S.
Department of Agriculture, Soil Conservation Service, Washington, D.C.,
January 1977.
48. Cuscino, T. A., Jr., J. S. Kinsey, and R. Hackney. The Role of Agri-
cultural Practices in Fugitive Dust Emissions. NTIS No. PB81-219073,
California Air Resources Board, Sacramento, CA, June 1981.
99
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SECTION 6
ESTIMATION OF CONTROL SYSTEM PERFORMANCE
— PROCESS SOURCES
Industrial process fugitive emissions pose a dual problem for the con-
trol engineer. These emissions contribute to degradation of ambient air
quality, and they can be a source of worker exposure to toxic or nuisance
contaminants. Consequently, control systems can be designed to reduce at-
mospheric emission rates and/or maintain low contaminant concentrations in
the worker breathing zone. Some control systems address both objectives,
while some address one at the expense of the other.
Fugitive emissions control systems have been installed on a wide varij
ety of process sources. Because these systems are designed with diverse
objectives and because individual process conditions vary, each fugitive
control system is unique in its design and operation. Some of the factors
which affect the choice of a system and selection of design and operating
parameters are size of the process, physical and chemical characteristics
of the emissions stream, worker or equipment access requirements for the
process, structural constraints (fugitive control systems often are
retrofit to existing processes), and regulatory requirements.
The variation in control system design and operation is reflected in
the extreme variation in the performance of those systems. This section
presents the available information on process fugitive emissions control
system performance. Because the control systems do vary widely in their
performance and these variations are not fully understood, the material in
this section should be used with caution. The performance data provided in
later subsections can provide the basis for engineering analyses of the
potential performance of a system. However, control efficiencies for a
system should not be applied directly to other systems.
101
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Assessment of the performance capability of a control system for a
specific industrial process requires a structured approach. Key process
and control system parameters that affect performance must be defined based
on general design principles. Available data on control system performance
then can be evaluated with respect to these key parameters.
The alternative approaches available for the control of process fugi-
tive emissions, as reviewed in Chapter 4, include:
1. Wet Suppression
• Water sprays (with and without chemical additives)
• Foams
2. Enclosures
• Passive enclosures (without evacuation)
• Active enclosures (with evacuation to a dust
collector)
3. Hooding Systems
• Receiving hoods
Canopy hoods
Close capture hoods
Hoods for mechanically directed plumes
• Capture hoods
Side draft hoods
Push/pull hooding systems
High velocity low volume hoods
Close capture hoods
4. Plume Aftertreatment
• Fine water sprays
• Electrostatic foggers
Wet suppression and passive enclosures are preventive measures, whereas
hooding systems and plume aftertreatment are capture/removal methods. All
of these controls are designed to be continuously applied.
This section presents the data needed to assess the four types of
process fugitive emissions control systems—wet suppression, enclosures,
hooding systems, and plume aftertreatment. For each type of system, basic
design considerations are described, key control parameters are identified,
and available performance data are presented. Two types of performance data
are included —those based on environmental measurements of reduction in
mass emissions and those based on measurements of workplace concentrations.
102
-------
Finally, a brief discussion of other control techniques for which test data
are not available is also presented.
6.1 WET SUPPRESSION SYSTEMS
The use of wet suppression for the control of fugitive emissions has
been discussed previously in Section 5. In this section, the application
of wet suppression systems for process sources will be addressed. Types of
processes which typically utilize wet suppression include crushers, screens,
and other size reduction operations.
6.1.1 Basic Design Considerations
As mentioned previously, either water, water plus a surfactant, or
aqueous foams can be used in wet suppression systems. Since each process
is unique, the specific design of the system and the wetting agent used
will vary from source to source. However, some general guidelines reported
in the literature include:
1. On primary and secondary crushers, water-only systems require
greater than 5% moisture, while water/surfactant systems can
achieve reasonable control with only 1% moisture.1'2
2. Tertiary crushing will require 4 to 5% moisture for water/surfac-
tant systems.3
3. Nozzles on crushers should be located between 3 and 6 ft from
moving materials to minimize nozzle damage and reduce the chance
of water drift.
6.1.2 Performance Data
Available test data for both water spray and foam wet suppression sys-
tems are presented in Table 6-1. The control efficiency data shown are
based on either a downwind tracer technique or respirable dust sampling in
the workplace atmosphere before and after control application. In both cases,
the data are extremely limited and of somewhat low quality. Therefore, cau-
tion is advised when utilizing the information contained in Table 6-1.
103
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TABLE 6-1. SUMMARY OF AVAILABLE CONTROL EFFICIENCY DATA FOR WATER SPRAYS AND FOAM SUPPRESSION
Reference type of
No. process
a
b
c
4 Crusher
5 Secondary
crusher
Tertiary
crusher
Type of
naterlal
Gypsum
Limestone
Limestone
Process
design/
operating
parameters
Hot specified
424 tons/hr,
3 in. Mate-
rial size
127 tons/hr,
5/8 In.
nominal Ma-
terial size
Control system
parameters
3 Nozzles (2 x 1/32
in. flat). 200
parts H20/l part
foaming agent
Water spray - not
specified
Water spray - not
specified
RAM samples are from Realtlne Aerosol Monitors, light scattering
type Instruments. Type 1 tests Include measurements of a single
source with and without control.
Test rating scheme
TCP = Tntal Cnenniw
Test
Measurement No. of data .
technique tests rating
RAN sampler without NA D
cyclone; Type 1
test scheme
Downwind tracer; 19 B
Type 1 test scheme
Downwind tracer; IB D
Type 1 Lest scheme
Efficiency based on concentrations only.
e Mo calibration or wind data.
Control
efficiency"1
(X)
RP 27d
TSP 83
PHIO 92
TSP 77
PHIO 83
defined In Section 4.4.
InH Dartiriilat
4> PU - Daxtlj
-------
A shown in Table 6-1, the test data on crusher controls are mixed.
One test indicated that foam applied at the crusher inlet results in only
27% control efficiency.4 Another test indicated that water sprays provided
83% control for primary and secondary crushers and 77% control for tertiary
crushers.5
6.2 ENCLOSURES
Enclosures can be used to contain or capture emissions from such
processes as crushing, screening, material cleaning, and material transport.
The enclosures used to control these emissions can be classified as one of
two types—active enclosures in which air is evacuated to an air pollution
control device and passive enclosures without evacuation. No substantive
mass emissions test data were identified for either active or passive enclo-
sures. Further, no information on design guidelines for enclosures was
obtained. Active enclosures ace described in more detail as a component of
capture/collection systems in Section 6.3.1.
6.3 CAPTURE/COLLECTION SYSTEMS
Capture/collection systems are frequently used in industrial facilities
to improve the work environment and reduce air emissions. The design of
each capture collection system is unique. It is dependent on the specific
operations to be controlled, the level of control required and physical
constraints of plant operations. While these systems are unique, they all
have three basic components: a hood or enclosure to capture or contain
particulate emissions; a ventilation system comprising the fan and ductwork
to provide airflow for capture and transport of the particulate matter; and
an air pollution control device. Each of these components is important to
the performance of the fugitive emission control system.
6.3.1 Basic Design Considerations
While only limited test data have been developed for capture collection
systems, a large body of information is available on design guidelines.6"9
105
-------
However, adherence to these guidelines does not assure the complete capture
of the emissions.' Although detailed design guidelines are not repeated here,
the following paragraphs do describe basic hooding design principles.
The objective of the exhaust hood is to capture particulate emissions
at the source before they escape to the plant environment or atmosphere.
The term hood is used in the broad sense to mean all suction openings in-
cluding suspended hoods, enclosures, side draft hoods, and open duct faces.
The hood acts to capture particulate via three mechanisms—enclosing the
emitting source(s) (enclosure), locating the hood so that buoyant or mechani-
cal forces imparted by the process direct the emissions into the hood (re-
ceiving hood), and using airflow generated by the hood to draw the emissions
stream into the hood (capture hood). Hoods often use more than one capture
mechanism.
Regardless of mechanism, the two primary parameters involved in the
design of effective local exhaust or hooding systems are: (a) locating the
hood (defined in the broad sense described above) to contain emitted par-
ticulate as much as possible; and (b) providing adequate flow to capture
any particulate not contained by the hood and prevent the escape of all
particulate from the hood. The goal of hood design is to install a hood or
enclosure that provides effective particulate control at the minimum exhaust
volume.
The first objective in locating the hood is to enclose the emissions
source as much as possible. The more complete the enclosure, the more eco-
nomical and effective the control system will be. In fact, one design
method is to start with a complete enclosure of the operation to be con-
trolled and add openings as required by the process.
When complete enclosure of the operation is not feasible, the follow-
ing practices are generally followed. All maintenance openings are located
away from the natural path of particulate that results from material flow
or dust splash. Inspection and maintenance openings are provided with doors
or rubber flaps if possible. Openings for material flow are often equipped
with flaps of rubber, canvas, or other pliable material.
Airflow exhausted from a local capture hood installed on an operation
involving material movement serves two purposes: the exhaust must overcome
induced airflow created by material motion; and the exhaust must provide
106
-------
sufficient velocity to capture particulate which escapes the confines of
the hood. The predominant function is dependent on hood type. If an
enclosure is used, control of induced airstreams is the primary objective.
If the operation requires an exterior hood, particulate capture is the
primary airflow function.
For those systems which can be controlled by complete or partial en-
closure, the airflow at the hood should be sufficient to overcome induced
air currents inherent to the process and to provide an inward air velocity
through all openings of about 50 to 200 ft/min.7 The volumes needed to
overcome induced air currents associated with specific processes are
discussed below. The flow needed to provide adequate velocities at openings
can be calculated by the formula:
Q = A V (6-1)
where:
Q = required airflow (ft3/rain)
A = cross-sectional area of openings (ft2)
V = required velocity at openings (ft/min)
Material transport creates an induced airflow which must be overcome
to effectively control fugitive emissions. Anderson has developed the fol-
lowing equation for calculating induced airflow at transfer points.8
= 10.0Au JS% (6-2)
where:
Q = induced airflow (ftVmin)
AU = feed opening (ft2)
R = rate of material flow (tons/hr)
S = height of fall (ft)
D = average particle diameter (ft)
107
-------
The objective of a capture hood is to provide a capture velocity of 50
to 75 ft/min at the farthest capture point from the hood. The total flow
required to achieve this velocity is:
Q = V (10 X2 + A) (6-3)
where:
Q = required airflow (ftVmin)
V = required capture velocity (ft/min)
X = distance from hood to farthest null point (ft)
A = cross-sectional area cf hood (ft2)
Receiving hoods capture particulate as it is directed from the source
by thermal or mechanical forces. Examples are canopy hoods for furnace
charging and tapping emissions and close capture hoods on grinding equipment.
Key design considerations are locating the hood so that the complete exhaust
stream is directed to the hood and generating an airflow greater than the
induced stream that is directed into the hood. Plume size and cross draft
problems are major concerns in designing receiving hoods.
6.3.2 Performance Data
The performance of the capture/collection system, as defined by control
efficiency, is a combination of the capture efficiency at the source and
the collection efficiency of the air pollution control device. Since data
on collection efficiency have been summarized in detail in previous man-
uals, they will not be addressed here.10-11 The discussion will focus on
the capture efficiency of hoods and enclosures.
Few test data are available on the performance of hoods and enclosures.
Estimates based on visible emissions observations do suggest that the per-
formance varies widely from plant to plant. Process and control system
parameters which contribute to this variation include location of the hood
with respect to the source, airflows in the vicinity of the source, process
and plume temperature, source mobility, and air volume flow rates. This
combination of limited test data and highly variable performance makes any
108
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general assessment of capture efficiency quite speculative. A separate guid-
ance document specifically related to the design of hood capture systems has
been developed under another EPA contract to which the reader is directed for
further information.12
Available data on control efficiencies for capture collection systems
are presented in Table 6-2.13-14 The data from the Banbury mixer highlight
the impact of plant conditions on hood performance. When an employee cool-
ing fan in'the vicinity of the mixer was turned on, capture efficiency was
reduced from 90 to 40%. The data also highlight the importance of distance
between the source and the hood on performance. When the hood was moved
from 1 to 3 m from the hood, efficiency was reduced from 90 to 70%.
6.4 PLUME AFTERTREATMENT
The injection of charged or uncharged water droplets into a dust plume
can effectively remove suspended particulate matter. Plume aftertreatment
includes the use of water sprays, steam, and charged water droplets (fog).
Since this technology has been described in detail above, any further dis-
cussion of such will not be presented here.
6.4.1 Basic Design Considerations
The same basic design parameters defined for plume aftertreatment of
open dust sources apply to the use of aftertreatment systems for process
sources. Droplet size, charge-to-mass ratio, and the method of applying an
electrostatic charge to the droplets, all must be taken into consideration.
The ambient temperature has a direct effect on droplet size and thus charge-
to-mass ratio.
6.4.2 Performance Data
Available test data for plume aftertreatment have been summarized in
Table 6-3.15~17 As shown, very limited data are available on the perfor-
mance of aftertreatment systems as applied to process fugitive sources.
At present the data are not adequate to quantify relationships between con-
trol/process parameters and performance.
109
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TABLE 6-2. SUMMARY OF CONTROL EFFICIENCY DATA FOR CAPTURE/COLLECTION SYSTEMS
Reference Type of Type of
Ho. process material
13 Aluminum Ho Hen
reduction aluminum
cell-anode
Aluminum Molten
reduction aluminum
cell tap-
ping
Anode Molten
removal aluminum
14 Banbury NA
mixer
Capture
Process mechanism/
design/ air pollution
operating control
parameters device
Not specified Close cap-
ture hood/
NA
Not specified Close cap-
ture/NA
Not specified Close cap-
ture/NA
Not specified Capture
hood/NA
Control system,
parameters
F low = SO mVntn
Flow = 80 oVoln
Flow = 120 mVmin
Flow = 160 n'/ntn
Flow = 120 aVnln
Flow = 120 B'/Bfn
Hood 1 a from mixer,
cooling fan off
Hood 1 m from mixer,
cooling fan on
Hood 3 m from mfxer.
cooling fan off
Measurement
technique
Tracer (Hz) in con-
trol system duct
Tracer (II2) in con-
trol system duct
Tracer (II2) in con-
trol system duct
Tracer (II2) In con-
trol system duct
Tracer (H2) In con-
trol system duct
Tracer (II2) in con-
trol system duct
Tracer (oil mist)
In control system
duct
Tracer (oil mist)
In control system
duct
Tracer (oil mist)
in control system
duct
No. of
tests
NA
NA
NA
NA
NA
NA
NA
NA
NA
Test
data
rating9
0
D
0
D
D>
0
0
D
0
Control .
efficiency
(%)
70
77
91
98
96
86
90
40
70
Test rating scheme defined in Section 4.4.
Capture efficiency measured indirectly with a tracer; no
measurements of source emissions.
-------
TAI^LE 6-3. SUMMARY OF AVAILABLE CONTROL EFFICIENCY DATA FOR PLUME AFTERTREATMENT SYSTEMS
(PROCESS SOURCES)3
Hef. Type of Process design/ h
No Type of process material operating parameters Fogger system
Test Average
Number rt data control f
Neasurenent technique of tests rating efficiency
IS Bag splitting hood Cream-te«
32X alumina
SJ% SiO,
Not specified
16 Cotton gin
Cotton press
Cotton fibers Hot specified
Cotton fibers Hot specified
17 Coke screen Coke
(Test Ho 4)9
Torch cutting 304 stainless
operation steel slabs
(Test Ho. S)g
1 run = 2-6 nin
Screen area = 1.8 m
- 4.0 m
Cutting rate =
9.5 en/ofn
Cutting tine = 40 oin
Slab thickness =
0 13 o
4 circles cut/slab
2-Ransburg REA foggers
located Inside hood;
WFR = 45 cc/nin total;
AF = 4.3 n'/hr total
Ritten Fogger II proto-
type^);
WFR = SO cc/oln
AF = 1.13 aVhr
Ritten Fogger II proto-
type^);
WFR - 100 cc/nin
AF = 4 5 m'/hr
2-Ritten Fogger IVs - one
spraying across screen
and one spraying down
on screen;
WFR ^ 53.91 t/hr/fogger
AF * 1.4-4.8 a>/hr/fogger
2-Ritten Fogger IVs
2-AeroVironoent CfGs
(pas. fog only) spray-
ing across source;
WFR * SB 6 L/hr/Ritten
fogger; 56.8-75.6 l/hr/
AV fogger
AF = 1.6 m'/hr/Rltten
fogger; SOX maximum (AV)
Inside hood. MSA
personnel sampler
Gravimetric samples, 10
instrunent unspecified
Gravimetric samples 6 lop 12
and center of press,
instrument unspecified
Hear screen. Hi-vol. 52
Hi-vol w/ssl; Hlrvol w/
SSI and Impactor
Above source: Hi-vol, 132
Hi-vol w/SSI, Hi-Vol
w/SSI and 4-stage ta-
pactor
RP=4S-6«
IP=83-88X
TP=33-7«
TSP=27-45X
IP=15-33*
TSP=58X'
IP=59X
(Ritten w/
neg. fog)
Includes only results of field testing.
The Rinsburg. Ritten, and Keystone foggers are based on the original Hoenig design which uses induction charging and commercial spray nozzles The
AeroVironmenl prototype units use a rotary atomizer and direct chanting to produce charged fog. AeroVIronnent CFG = 200 urn drops; 1.2(10) 6 C/g 9 4 kV;
16-24 n1 spray volume Ritten Fogger IV = - 60 M« drops; 0.11(10) • C/g 0 12 5 W. WFR = water flow rate. AF = airflow to fogger(s).
MSA personnel sampler = 10 on nylon cyclone followed by a 37-nm niter cassette 10 mm nylon cyclone also used on GCA Model ROM-101 and RAM-I continuous
mtiiumenls u/0 - measuienenis taken upstream and downstream of the point where charged log is Injected into conveyoi tunnel Mi-vol = standard high
volume jir sampler, Hi-vol w/SSI = high volume air sampler equipped with Sierra 15 umA size-selective inlet, Hf-vol w/cyclone and iopaclor = high volume
air sampler equipped with Sierra Model 230CP cyclone precollector and Sierra Model 230 slotted cascade Impactor
Foul number of uncontrolled and controlled tests conducted.
Ujta uled uiing crilei la specified in Section 4 4
fP = loUl PJI uculale. ISP = Fulal Suspended Paniculate,
IP - Innaldble Particuldte
Located inside a building
No background samples collected during lest program
Calculated (rum paniculate concentrations in Table 24, page "it ot test
tepori (Rer No 17)
-------
6.5 OTHER PROCESS CONTROLS
There are a number of other techniques which can be used for the control
of process sources where no substantive test data are available on control
efficiency. These methods include both process and work practice modifica-
tions as well as housekeeping measures. Table 6-4 provides selected refer-
ences which might be used to guide the reader in the application of these
techniques.
TABLE 6-4. LITERATURE REFERENCES FOR PROCESS SOURCE CONTROLS
WHERE NO TEST DATA ARE AVAILABLE
Control method Literature reference(s)3
Process modifications 11, 18, 19, 20, 21, 22, 23
Work practice modifications 11, IS, 22, 23
Housekeeping 22
a Refers to references listed at the end of Section 6.
REFERENCES FOR SECTION 6
1. U.S. Environmental Protection Agency. Non-Metallic Mineral Processing
Plants, Background Information for Proposed Standards. EPA-450/3-83-
OOla, NTIS No. PB83-258103, Research Triangle Park, NC, March 1983.
2. JACA Corporation. Control of Air Emissions from Process Operations in
the Rock Crushing Industry. EPA-340/1-79-002, U.S. Environmental Pro-
tection Agency, Washington, O.C., January 1979.
3. Pilz, K. Wet Dust Suppression Brightens Mineral Processing Picture.
Mining Engineering, July 1972.
4. Page, S. 0. Evaluation of the Use of Foam for Dust Control on Face
Drills and Crushers. RI 8595, U.S. Bureau of Mines, Washington, D.C.,
1982.
112
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5. Eimutis, E. C., T. R. Blackwood, and R. Wachter. Participate Emissions
from Stone Crushing Operations. Monsanto Research Corporation, Dayton,
OH, November 1979.
6. Hemeon, W. C. L. Plant and Process Ventilation. The Industrial Press,
New York, NY, 1963.
7. American Conference of Governmental Industrial Hygienists. Industrial
Ventilation, A Manual of Recommended Practice. 18th Edition. Lansing,
MI, 1984.
8. Anderson, D. M. Dust Control Design by the Air Induction Technique.
Industrial Medicine and Surgery, pp. 68-72. February 1964.
9. Morrison, J. N. Controlling Dust Emissions at Belt Conveyor Transfer
Points. Transactions Society of Mining Engineers, AIME, Vol. 250,
pp. 47-53. March 1971.
10. Control Techniques for Particulate Emissions from Stationary Sources.
Volumes I and II. EPA-450/3-81-005, U.S. Environmental Protection
Agency, Research Triangle Park, NC, September 1982.
11. Daniel son, J. A. Air Pollution Engineering Manual. EPA Report AP-40,
NTIS No. 225132, U.S. Environmental Protection Agency, Research Triangle
Park, NC, May 1973.
12. Kashdan, E. R., et al. Technical Manual: Hood System Capture of Pro-
cess Fugitive Particulate Emissions. EPA-600/7-86-016, NTIS No. PB86-
190444, U.S. Environmental Protection Agency, Research Triangle Park,
NC, April 1986.
13. Johnson, A. R., T. A. Lowe, W. W. Hanneman, and R. J. Schlager. A
Study of Reduction Cell Fluoride Emissions. Conference Proceedings,
The Metallurgical Society of AIME, Light Metals, 1980.
14. Ellenbecker, M. J., R. F. Gempel, and W. A. Burgess. Capture Efficiency
of Local Exhaust Ventilation Systems. American Industrial Hygiene Asso-
ciation Journal. 44(10):752-755, October 1983.
15. Hoenig, S. A. Use of Electrostatically Charged Fog for Control of
Fugitive Dust Emissions. EPA-600/7-77-131, NTIS No. PB276645, U.S.
Environmental Protection Agency, Research Triangle Park, NC, November
1977.
16. Hoenig, S. A. Fugitive and Fine Particle Control Using Electrostati-
cally Charged Fog. EPA-600/7-79-078, NTIS No. PB298069, U.S. Environ-
mental Protection Agency, Research Triangle Park, NC, March 1979.
17. Brookman, E. T., and K. J. Kelley. Demonstration of the Use of Charged
Fog in Controlling Fugitive Dust from Large-Scale Industrial Sources.
EPA-600/2-83-044, NTIS No. PB83-217828, U.S. Environmental Protection
Agency, Research Triangle Park, NC, June 1983.
113
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18. Jutze, G. A., et al. Technical Guidance for Control of Industrial Pro-
cess Fugitive Particulate Emissions. EPA-450/3-77-010, NTIS No.
PB272288, U.S. Environmental Protection Agency, Research Triangle Park,
NC, March 1977.
19. Ohio Environmental Protection Agency. Reasonably Available Control
Measures for Fugitive Oust Sources. Columbus, OH, September 1980.
20. Forrest, R. D., and H. Wolfensberger. Improved Ladle Treatment of
Ductile Iron by Means of the Tundish Cover. AFS Transactions. 80-57,
p. 421-426.
21. Bright, J., and F. M. Shaw. The Effect of Moisture on the Amount of
Oust Produced by Foundry Sand. Journal of Research and Development.
British Cast Iron Research Association, December 1952.
22. Burton, D. J., et al. Demonstrations of Control Technology for Sec-
ondary Lead Reprocessing, Volumes 1 and 2. Contract No. 210-81-7106,
National Institute for Occupational Safety and Health, Cincinnati, OH,
September 1983.
23. Kost, J. A., J. C. Yingling, and B. J. Mondics. Guidecook for Dust
Control in Underground Mining. OFR 145-82, U.S. Bureau of Mines,
Washington, D.C., December 1981.
114
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SECTION 7
ESTIMATION OF CONTROL COSTS AND
COST EFFECTIVENESS
Development and evaluation of participate fugitive emissions control
strategies require analyses of the relative ^costs of alternative control
measures. Cost analyses are used by control agency personnel to develop
overall strategies for an air pollution control district or to evaluate
plant specific control strategies. Industry personnel perform cost anal-
yses to evaluate control alternatives for a specific source or to develop a
plant-wide emissions control strategy. Although the specifics of these anal'
yses may vary depending upon the objective of the analysis and the avail-
ability of cost data, the general format is similar.
The primary goal of any cost analysis is to provide a consistent com-
parison of the real costs of alternative control measures. The objective
of this section is to provide the reader with a methodology that will allow
such a comparison. It will describe the overall structure of a cost anal-
ysis and provide the resources for conducting the analyses. Because cost
data are continuously changing, specific cost data are not provided. How-
ever, sources of cost information and mechanisms for cost updating are pro-
vided.
The approach outlined in this section will focus on cost-effectiveness
as the primary comparison tool. Cost-effectiveness is simply the ratio of
the annualized cost of the emissions control to the amount of emissions re-
duction achieved. Mathematically, cost-effectiveness is defined by:
c* - fa (7-1)
L ~ &R
where:
C* = cost effectiveness ($/mass of emissions reduction)
115
-------
C, = annualized cost of the control measure ($/year)
Cm
AR = reduction (mass/year) in annual emissions
This general methodology was chosen because it is equally applicable to dif-
ferent controls that achieve equivalent emissions reduction on a single
source and to measures that achieve varied reductions over multiple sources.
The discussion is divided into three sections. The first section de-
scribes the general cost analysis methodology, including the various types
of costs that should be considered and presents methods for calculating
those costs. The second identifies the primary cost elements associated
with each of the fugitive emissions control systems identified in Section 4.
The final section identifies sources of cost data and discusses methods for
updating cost data to constant dollars.
7.1 GENERAL COST METHODOLOGY
Calculation of cost-effectiveness for comparison of control measures
or control strategies can be accomplished in four steps. First, the alter-
native control/cost scenarios are selected. Second, the capital costs of
each scenario is calculated. Third, the annualized costs for each of the
alternatives is developed. Finally, the cost-effectiveness is calculated,
taking into consideration the level of emissions reduction.
The general approach for performing each of the above steps is described
below. This approach is intended to provide general guidance for cost com-
parison. It should not be viewed as a rigid procedure that must be followed
in detail for all analyses. The reader may choose or may be forced through
resource or informational constraints to omit some elements of the analysis.
However, for comparisons to be valid, cautions that should be observed are:
(1) All control scenarios should be treated in the same manner; and (2) cost
elements that vary radically between cost scenarios should not be omitted.
7.1.1 Select Control/Cost Scenarios
Prior to the cost analysis general control measures or strategies will
have been identified. These measures or strategies will fall into one of
116
-------
the major classes of fugitive emission control techniques that were identi-
fied in Tables 4-1 and 4-2. The first step in the cost analysis is to se-
lect a set of specific control/cost scenarios from the general techniques.
The specific scenarios will include definition of the major cost elements
and identification of specific implementation alternatives for each of the
cost elements.
Each of the general control techniques identified in Chapter 4 has
several major cost elements. These elements include capital equipment ele-
ments and operation/maintenance elements. For example, the major cost ele-
ments for chemical stabilization of an unpaved road include: (a) chemical
acquisition; (b) chemical storage; (c) road preparation; (d) mixing the
chemical with water; and (e) application of the chemical solution. The
first step in any cost analysis is definition of these major cost elements.
Information is provided in Section 7.2 on the major cost elements associated
with each of the general techniques defined in Section 4.
For each major cost element, several implementation alternatives can
be chosen. Options within each cost element include such choices as buy-
ing or renting equipment; shipping chemicals by rail car, truck tanker, or
in drums via truck; alternative sources of power or other utilities; and
use of plant personnel or contractors for construction and maintenance.
The major cost elements and the implementation alternatives for each of
these elements for the chemical stabilization example described above are
outlined in Table 7-1.
7.1.2 Develop Capital Costs
The capital costs of a fugitive emissions control system are those di-
rect and indirect expenses incurred up to the date when the control system
is placed in operation. These capital costs include actual purchase ex-
penses for capital equipment, labor and utility costs associated with in-
stallation of the control system, and system start-up and shakedown costs.
In general, direct capital costs are the costs of control equipment and the
labor, material, and utilities needed to install the equipment. Indirect
costs are overall costs to the facility incurred by the system but not di-
rectly attributable to specific equipment items.
117
-------
TABLE 7-1. IMPLEMENTATION ALTERNATIVES FOR STABILIZATION OF AN UNPAVED ROAD
Cost elements
Implementation alternatives
I. Purchase and ship chemical
II. Store chemical
III. Prepare road
IV.
Mix chemical and water in
application truck
V.
Apply chemical solution via
surface spraying
A. Ship in railcar tanker (11,000-
22,000 gal/tanker
B. Ship in truck tanker (4,000-
6,000 gal/tanker)
C. Ship in drums via truck (55 gal/
drum)
A. Store on plant property
1. In new storage tank
2. In existing storage tank
a. Needs refurbishing
b. Needs no refurbishing
3. In railcar tanker
a. Own railcar
b. Pay demurrage
4. In truck tanker
a. Own truck
b. Pay demurrage
5. In drums
B. Store in contractor tanks
A. Use plant-owned grader to mini-
mize ruts and low spots
B. Rent contractor grader
C. Perform no road preparation
A. Put chemical in spray truck
1. Pump chemical from storage
tank or drums into applica-
tion truck
2. Pour chemical from drums into
application truck, generally
using forklift
B. Put water in application truck
1. Pump from river or lake
2. Take from city water line
A. Use plant owned application truck
B. Rent contractor application truck
118
-------
Direct costs cover the purchase of equipment and auxiliaries and the
costs of installation. These costs include system instrumentation and in-
terconnection of the system. Capital costs also include any cost of site
development necessitated by the control system. For example, if a fabric
filter on a capture/collection system requires an access road for removal
of the collected dust, this access road is included as a capital expense.
The types of direct costs typically associated with fugitive emissions con-
trol systems include:
• Equipment costs • Painting
• Equipment installation • Insulation
• Instrumentation • Structural support
• Duct work • Foundations
• Piping • Supporting administrative structures
• Electrical • Control panels
• Site development • Access roads or walkways
• Buildings
Indirect costs cover the expenses not attributable to specific equip-
ment items. Items in this category are described below1:
1. Engineering costs - includes administrative, process, project,
and general; design and related functions for specifications; bid
analysis; special studies; cost analysis; accounting; reports;
purchasing; procurement; travel expenses; living expenses; expe-
diting; inspection; safety; communications; modeling; pilot plant
studies; royalty payments during construction; training of plant
personnel; field engineering; safety engineering; and consultant
services.
2. Construction and field expenses - includes costs for temporary
field offices; warehouses; craft sheds; fabrication shops; mis-
cellaneous buildings; temporary utilities; temporary sanitary
facilities; temporary roads; fences; parking lots; storage areas;
field computer services; equipment fuel and lubricants; mobiliza-
tion and demobilization; field office supplies; telephone and tel-
egraph; time-clock system; field supervision; equipment rental;
small tools; equipment repair; scaffolding; and freight.
119
-------
3. Contractor's fee - includes costs for field-labor payroll; super-
vision field office; administrative personnel; travel expenses;
permits; licenses; taxes; insurance; field overhead; legal liabil-
ities; and labor relations.
4. Shakedown/startup - includes costs associated with system startup
and shakedown.
5. Contingency costs - the excess account set up to deal with uncer-
tainties in the cost estimate, including unforeseen escalation in
prices, malfunctions, equipment design alterations, and similar
sources.
The values for these items will vary depending on the specific opera-
tions to be controlled and the types of control systems used. Typical
ranges for indirect costs based on the total installed cost of the capital
equipment are shown in Table 7-2.
TABLE 7-2. TYPICAL VALUES FOR INDIRECT CAPITAL COSTS1
Cost item
Range of values
Engineering
Construction and
field expenses
Contractor's fee
Shakedown/startup
Contingency
8 to 20% of installed cost. High
value for small projects; low value for
large projects.
7 to 70% of installed cost.
10 to 15% of installed cost.
1 to 6% of installed cost.
10 to 30% of total direct and indirect
costs dependent upon accuracy of esti-
mate. Generally, 20% is used in a
study estimate.
7.1.3 Determine Annualized Costs
The most common basis for comparison of alternative control system
is that of annual i zed cost. The annual i zed cost of a fugitive emission
120
-------
control system includes operating costs such as labor, materials, utilities,
and maintenance items as well as the annualized cost of the capital equip-
ment. The annualization of capital costs is a classical engineering eco-
nomics problem, the solution of which takes into account the fact that
money has time value. These annualized costs are dependent on the interest
rate paid on borrowed money or collectable by the plant as interest (if
available capital is used), the useful life of the equipment and deprecia-
tion rates of the equipment.
The components of the annualized cost of implementing a particular con-
trol technique are depicted graphically in Figure 7-1. Purchase and instal-
lation costs include freight, sales tax, and interest on borrowed money.
The operation and maintenance costs reflect increasing frequency of repair
as the equipment ages along with increased costs due to inflation for parts,
energy, and labor. On the other hand, costs recovered by claiming tax cre-
dits or deductions are considered as income. Mathematically the annualized
costs of control equipment can be calculated from:
ca = CRF (V * Co * °'5 Co (7"2)
where:
C, = annualized costs of control equipment ($/year)
a
CRF = Capital Recovery Factor (I/year)
C = installed capital costs ($)
C = direct operating costs ($/year)
0.5 = plant overhead factor
The various components of this equation are briefly described below.
The annualized cost of capital equipment is calculated by using a capi-
tal recovery factor (CRF). The capital recovery factor combines interest
on borrowed funds and depreciation into a single factor. It is a function
of the interest rate and the overall life of the capital equipment and can
be estimated by the following equation:
121
-------
8
8
Equipment. Installation, Freight, Tax, and Interest
Depreciation Tax Deduction
LIFE OF EQUIPMENT
Scrap
Value
I
Figure 7-1. Graphical presentation of fugitive emission control costs
-------
CRF = (7-3)
(1 + i) - 1
where:
i = interest rate (annual % as a fraction)
n = economic life of the control system (year)
The other major components of the annualized cost are operation and
maintenance costs (direct operating costs) and associated plant overhead
costs. Operation and maintenance costs generally include labor, raw ma-
terials, utilities, and by-product costs or credits associated with day-
to-day operation of the control system. Elements typically included in
this category are1:
1. Utilities - includes water for process use and cooling; steam;
electricity to operate controls, fans, motors, pumps, valves, and
lighting; and fuel, if required.
2. Raw materials - includes any chemicals needed to operate the
system.
3. Operating labor - includes supervision and the skilled and un-
skilled labor needed to operate, monitor, and control the system.
4. Maintenance and repairs - includes the manpower and materials to
keep the system operating efficiently. The function of mainte-
nance is both preventive and corrective, to keep down-time to a
minimum.
5. By-product costs - in systems producing a salable product, this
would be a credit for that product; in systems producing a product
for disposal, this would be the cost of disposal.
6. Fuel costs - includes the incremental cost of the fuel, where more
than the normal supply is used.
Another component of the operating cost is overhead, which is a busi-
ness expense not charged directly to a particular part of the process but
allocated to it. Overhead costs include administrative, safety, engineer-
ing, legal, and medical services; payroll, employee benefits; recreation;
123
-------
and public relations. As suggested by Eq. 7-2, these charges are estimated
to be approximately 50% of direct operating costs.
7.1.4 Calculate Cost Effectiveness
As discussed in the introduction to this section the most informative
method for comparing control measures or control strategies for particulate
fugitive emissions sources is on a cost-effectiveness basis. Mathematically,
cost-effectiveness is defined as:
Ca
C* = £Jj (7-1)
where:
C* = cost-effectiveness ($/mass of emissions reduced)
C = annualized cost of control equipment ($/year)
cl
AR = annual reduction in particulate emissions (mass/year)
The annualized cost of control equipment can be calculated using
Eq. 7-2. The annual reduction in particulate emissions can be calculated
from the following equation:
AR = M e c (7-4)
where:
M = annual source extent
e = uncontrolled emission factor (i.e., mass of uncontrolled
emissions per unit of source extent)
c = average control efficiency expressed as a fraction
The methodology for calculating annualized costs and sources of data
on costs of fugitive emissions control systems are contained in this sec-
tion. Information relative to uncontrolled emission factors is discussed
in Section 3 and estimates of control efficiencies for various control sys-
tems are presented in Sections 5 and 6.
124
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7.2 COST ELEMENTS OF FUGITIVE EMISSIONS CONTROL SYSTEMS
The cost methodology outlined In Section 7.1 requires that the analyst
define and select alternative control/cost scenarios and develop costs for
the major cost elements within these scenarios. The objective of this sub-
section is to assist the reader in identifying the implementation alterna-
tives and major cost elements associated with the emission reduction tech-
niques identified in Section 4. For open dust sources, the control tech-
niques addressed are: wet dust suppression; surface cleaning; and paving.
For process fugitive sources, the primary control techniques addressed are:
wet suppression; capture/collection; and plume aftertreatment.
Implementation alternatives for open dust source emission control mea-
sures are presented in Tables 7-3 through 7-5. Table 7-3 presents implemen-
tation alternatives for water and chemical dust suppressant systems. Table
7-4 presents alternatives for three types of street cleaning systems—sweeping,
flushing, and a combination of flushing and broom sweeping. Table 7-5 pre-
sents alternatives for streets or parking lot paving.
Implementation alternatives for process fugitive source control mea-
sures are presented in Tables 7-6 through 7-8. Table 7-6 outlines alterna-
tives fo.r wet suppression systems. Table 7-7 presents alternatives for a
capture/collection system; these alternatives are applicable for active en-
closures, capture hoods, and receiving hoods. Table 7-8 presents implementa-
tion alternatives for plume aftertreatment systems.
After the control scenarios are selected, the analyst must estimate
the capital cost of the installed system and the operating and maintenance
costs. The indirect capital costs elements are common to all systems and
were identified in Table 7-2. The direct capital cost elements and direct
operation and maintenance cost elements which are unique to each type of
fugitive emission control system are identified in Tables 7-9 through 7-14.
These costs are provided for dust suppressant programs for open dust sources
in Table 7-9, street cleaning programs in Table 7-10, paving in Table 7-11,
wet suppression systems for process sources in Table 7-12, capture/collection
systems in Table 7-13, and plume aftertreatment systems in Table 7-14.
125
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TABLE 7-3. IMPLEMENTATION ALTERNATIVES FOR DUST SUPPRESSANTS
APPLIED TO AN UNPAVED ROAD
Dust suppressant type
Program Implementation alternative Chemicals Water
I. Purchase and ship dust suppressant
A. Ship in rail car tanker (11.000-22.000 X
gal/tanker)
B. Ship in truck tanker (4,000-6.000 gal/ X
tanker)
C. Ship in drums via truck (55 gal/drum) X
II. Store dust suppressant
A. Store on plant property
1. In new storage tank X
2. In existing storage tank
a. Needs refurbishing X
b. Needs no refurbishing X
3. In railcar tanker
a. Own railcar X
b. Pay deourraga X
4. In truck tanker
a. Own truck X
b. Pay demurrage X
5. In drums X
B. Store in contractor tanks X
III. Prepare road
A. Use plant-owned grader to minimize ruts X X
and low spots
B. Rent contractor grader X X
C. Perform no road preparation X X
IV. Nix dust suppressant/water in application
truck
A. Put suppressant in spray truck
1. Pump suppressant from storage tank X
or drums into application truck
2. Pour suppressant from drums into X
application truck, generally using
fork!1ft
B. Put water in application truck
1. Pump from river or lake X X
2. Take from city water line X X
V. Apply suppressant solution via surface
spraying
A. Use plant owned application truck X X
B. Rent contractor application truck X X
126
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TABLE 7-4. IMPLEMENTATION ALTERNATIVES FOR STREET CLEANING
Program Broom- Flushing and
imDlementation alternative sweeping Flushing broom-sweeping
I. Acquire flusher and driver
A. Purchase flusher and use plant X X
driver
B. Rent flusher and driver X X
C. Use existing unpaved road X X
watering truck
II. Acquire broom sweeper and driver
A. Purchase broom sweeper and X X
use plant driver
B. Rent broom sweeper and driver X X
III. rill flusher tank with water
A. Pump water from river or lake X X
B. Take water from city line X X
IV. Maintain purchased flusher X X
V. Maintain purchased broom sweeper X X
TABLE 7-5. IMPLEMENTATION ALTERNATIVES
FOR PAVING
Program implementation alternative
I. Excavate existing surface to make way for
base and surface courses
A. 2-in. depth
B. 4-in. depth
C. 6-in. depth
II. Fine grade and compact subgrade
III. Lay and compact crushed stone base course
A. 2-in. depth
B. 4-in. depth
C. 6-in. depth
IV. Lay and compact hot mix asphalt (probably
AC120-150) surface course
A. 2-in. depth
B. 4-in. depth
C. 6-in. depth
127
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TABLE 7-6. IMPLEMENTATION ALTERNATIVES FOR WET SUPPRESSION
I. Basic design decisions
A. What type wet suppression system will be used?
• Water spray
• Water/surfactant spray
• Micron-si zed foam
• Combination system
B. What sources will be controlled?
C. What system layout will be used?
• Centralized supply with headers for each source
• Individual systems for some sources
II. Construction/installation decisions
A. Who will install system?
• Contractor
• Plant personnel
III. Operational decisions
A. What is the water source?
• Plant wells
• Local surface waters
• City water system
B. Under what weather conditions will the system be needed?
• Above freezing only
• Below freezing
C. How will routine maintenance be provided?
• Plant personnel
• Maintenance contractor
128
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TABLE 7-7. IMPLEMENTATION ALTERNATIVES FOR CAPTURE/
COLLECTION SYSTEMS
I. Basic design decisions
A. What type hooding system best fits each source?
• Enclosure
• Capture hood
• Receiving hood
B. What type of air pollution control device best meets plant needs?
• Cyclone
• wet scrubber
• Fabric filter
C. How will collected participate be handled?
• Screw conveyor
• Pneumatic transport
• Slurry piping
• Batch removal
0. What system layout will be used?
• Multiple collection points ducted to centralized air pollution
control device
• Dedicated air pollution control devices for each source
• Mixed system
E. Who will design the system?
• Outside design of total system
• Plant design of system with vendor design of individual
components
II. Construction/installation
A. Who will install system?
• Plant personnel
• Contractor
3. Who is responsible for system shakedown/startup?
• Plant environmental staff
• Plant operators
• Contractor personnel
III. Operational decisions (dependent on type of system selected)
A. What electrical source will be used?
• Public utility
• Plant power system
B. What water source will be used?
• Plant well
• Local surface water
• Public water system
C. How will routine maintenance be provided?
• Plant personnel
• Outside contractor
0. How will collected paniculate be disposed?
• Returned to process
• Landfilled
• Surface impoundment
129
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TABLE 7-8. IMPLEMENTATION ALTERNATIVES FOR PLUME AFTERTREATMENT
SYSTEMS
I. Basic design decisions
A. What sources are to be controlled?
B. What is the physical size of the source and resulting dust
• plume?
C. Is the area sheltered from wind or cross drafts such that
aftertreatment can be effectively applied?
D. Mow many foggers or nozzles are to be used and where are
they to be positioned?
E. How will water and electric power be supplied to unit(s)?
• Central system
• Separate line(s) from multiple sources
II. Construction/installation decisions
A. Who will install system?
• Contractor
• Plant personnel
III. Operational decisions
A. What is the water source?
• Plant wells
• Local surface waters
• City water system
B. What electrical source will be used?
• Public utility
• Plant power
C. Under what weather conditions will the system be needed?
• Above freezing only
• Below freezing
0. How will routine maintenance be provided?
• Plant personnel
• Maintenance contractor
130
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TABLE 7-9. CAPITAL EQUIPMENT AND O&M EXPENDITURE
ITEMS FOR OUST SUPPRESSANT SYSTEMS6
(OPEN SOURCES)
Capital equipment
• Storage equipment
Tanks
Rail car
Pumps
Piping
• Application equipment
Trucks
Spray system
Piping (including winterizing)
O&M expenditures
• Utility or fuel costs
Water
Electricity
Gasoline or diesel fuel
• Supplies
Chemicals
Repair parts
• Labor
Application time
Road conditioning
System maintenance
Not all items are necessary for all systems.
Specific items are dependent on the control
scenario selected.
131
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TABLE 7-10. CAPITAL EQUIPMENT AND O&M
EXPENDITURE ITEMS FOR
STREET CLEANING
Capital equipment
• Sweeping
Brooa
Vacuum system
• Flushing
Piping
Flushing truck
Water pumps
O&M expenditures
• Utility and fuel costs
Water
Gasoline or diesel fuel
• Supplies
Replacement brushes
• Labor
Sweeping or flushing operation
Truck maintenance
• Waste disposal
TABLE 7-11. CAPITAL EQUIPMENT AND O&M
EXPENDITURE ITEMS FOR
PAVING
Capital equipment
• Operating equipment
Graders
Paving application equipment
Materials
Paving material (asphalt or concrete)
Base material
O&M expenditures
• Suoplies
Patching material
• Labor
Surface preparation
Paving
Road maintenance
Equipment maintenance
132
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TABLE 7-12. CAPITAL EQUIPMENT AND O&M EXPENDITURE
ITEMS FOR WET SUPPRESSION
SYSTEMS (PROCESS SOURCES)
Capital equipment
• Water spray systems
Supply pumps
Nozzles
Piping (including winterization)
Control system
Filtering units
• Water/surfactant and foam systems only
Air compressor
Mixing tank
Metering or proportioning unit
Surfactant storage area
O&M expenditures
• Utility costs
Water
Electricity
• Supplies
Surfactant
Screens
• Labor
Maintenance
Operation
133
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TABLE 7-13. CAPITAL EQUIPMENT AND O&M EXPENDI-
TURE ITEMS FOR CAPTURE COLLEC-
TION SYSTEMS3
Capital equipment
• Dust collector
Baghouse or scrubber
Concrete work
Dust removal system
Control instrumentation
Monitoring instrumentation
• Hood(s)
• Ventilation system
Fan
Electrical wiring
Ductwork
Concrete support work
Damper system
Expansion joints
• Dust storage system
O&M expenditures
• Utilities
Electricity
Water
• Supplies
Replacement bags
Fan motors
Chemical additives for scrubber
• Labor
System operation
Control device maintenance and cleaning
Ductwork maintenance
• Disposal of collected particulate
Specific items included will depend on the
control scenario selected.
134
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TABLE 7-14. CAPITAL AND O&M EXPENDITURES FOR PLUME
AFTERTREATMENT SYSTEMS
Capital equipment:
• Fogging or spray heads (nonelectrostatic)
Atomizers
Supply pumps
Plumbing (including weatherization)
Water filters
Flow control system
• Electrostatic foggers or spray nozzles
Atomizer(s) and high voltage power supply
Water pumps and plumbing (including weatherization)
Water filters
Flow control system
Power lines and electric utilities
O&M expenditures:
• Utility costs
Water
Electricity
• Supplies
Antifreeze agent(s)
Screens
Replacement electrodes (if applicable)
• Labor
Operation
Maintenance
135
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7.3 SOURCES OF COST DATA
Collection of the data to conduct a cost analysis can sometimes be
difficult. If a well defined system is being costed, the best sources of
accurate capital costs are vendor estimates. However, if the system is not
sufficiently defined to develop vendor estimates, published cost data can be
used. Table 7-15 presents sources of cost data for both open dust and pro-
cess fugitive emissions control systems. The first three items relate pri-
marily to open dust control systems while the last three references can be
used to estimate component costs for both open dust and process fugitive
emissions control systems.
Often published cost estimates are based on different time-valued dol-
lars. These estimates must be adjusted for inflation so that they reflect
the most probable capital investments for a current time and can be con-
sistently compared. Capital cost indices are the techniques used for
updating costs. These indices provide a general method for updating over-
all costs without having to complete in-depth studies of individual cost
elements. Indices that typically are used for updating control system
costs are the Chemical Engineering Plant Cost Index, the Bureau of Labor
Statistics Metal Fabrication Index, and the Commerce Department Monthly
Labor Review.
Operation and maintenance cost estimates typically are based on vendor
or industry experience with similar systems. In the absence of such data,
rough estimates can be developed from sources 3 and 6 in Table 7-15.
REFERENCES FOR SECTION 7
1. PEDCo Environmental, Inc. Cost Analysis Manual for Standards Support
Document. U.S. Environmental Protection Agency. November 1978.
136
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TABLE 7-15. PUBLISHED SOURCES OF FUGITIVE EMISSION CONTROL
SYSTEM COST DATA
1. Cuscino, Thomas, Jr., Gregory E. Muleski, and Chatten Cowherd, Jr.
Iron and Steel Plant Open Source Fugitive Emission Control Evaluation.
EPA-600/2-83-110, NTIS No. PB84-110568, U.S. Environmental Protection
Agency, Research Triangle Park, NC, October 1983.
2. Muleski, Gregory E., Thomas Cuscino, Jr., and Chatten Cowherd, Jr.
Extended Evaluation of Unpaved Road Dust Suppressants in the Iron
and Steel Industry. EPA-600/2-84-027, NTIS No. PB84-154350, U.S.
Environmental Protection Agency, Research Triangle Park, NC, February
1984.
3. Cuscino, Thomas, Jr. Cost Estimates for Selected Dust Controls Ap-
plied to Unpaved and Paved Roads in Iron and Steel Plants. EPA Con-
tract No. 68-01-6314, Task 17, U.S. Environmental Protection Agency,
Region V, Chicago, Illinois, April 1984.
4. Richardson Engineering Services, Inc. The Richardson Rapid Construc-
tion Cost Estimating System: Volume I - Process Plant Construction
Estimating Standards. 1983-84 Edition.
5. Robert Snow Means Company, Inc. Building Construction Cost Data.
1979.
6. Neveril, R. V. Capital and Operating Costs of Selected Air Pollution
Control Systems. EPA-450/5-80-002. CARD, Inc., December 1978.
137
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SECTION 8
FUGITIVE EMISSIONS CONTROL STRATEGY DEVELOPMENT
As outlined in the previous sections, development of a fugitive emis-
sions control strategy for an industrial facility can be accomplished
through a five step process. These five steps are:
Step 1: Identify and classify all fugitive sources.
Step 2: Prepare an emissions inventory.
Step 3: Identify control alternatives.
Step 4: Estimate control system performance.
Step 5: Estimate control costs and cost-effectiveness.
This section will illustrate those five steps for a hypothetical 300-ton/hr
rock crushing plant. As shown in Figure 8-1, the facility includes a pri-
mary, secondary, and tertiary crusher, and associated materials sizing,
handling, and storage facilities. The following subsections describe the
control strategy evalution for this facility.
8.1 IDENTIFY/CLASSIFY FUGITIVE EMISSION SOURCES
The fugitive particulate emission sources for this facility are identi-
fied schematically in Figure 8-1. They include:
• A primary crusher;
• A secondary crusher;
• A tertiary crusher;
• Two screens;
139
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Pilmaiy f:'nBS
Conveyor
KEY.
©
I Indicates luglllva emission pom)
Figure 8-1. Simplified process flow diagram for a typical rock
crushing plant
-------
• A truck dump station;
• Six conveyor transfer points;
• Vehicular traffic on unpaved haul road between the quarry and the
plant;
• Windblown emissions from product storage;
• A front-end loader for loadout of customer trucks; and
• Vehicular traffic on a paved road between the loadout area and the
property line.
These sources are consistent with those identified for the minerals products
industry in Table 2-1 and the general open dust sources in Table 2-2.
8.2 PREPARE EMISSIONS INVENTORY
Calculation of the estimated emission rate for a given source requires
data on source extent, uncontrolled emission factor, and control efficiency.
The mathematical expression for this calculation is as follows:
R = M e (1 - c) (8-1)
where:
R = estimated mass emission rate
M = source extent
e = uncontrolled emission factor (i.e., mass of uncontrolled
emissions per unit of source extent)
c = fractional efficiency of control
For this plant we assume that the initial control efficiency for all sources
is 0%. The uncontrolled emission factors for the five open dust sources
and the 11 process sources as well as the required source extents are pre-
sented below.
141
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8.2.1 Unpaved Haul Road
The uncontrolled emission factor for unpaved roads as presented in
Reference 1 is:
••«»> fef) y r/7 (if'5 (i?) <«"*" <8-2>
where:
k = particle size multiplier (dimensionless)
s = silt content of road surface material (%)
S = mean vehicle speed (mph)
W = mean vehicle weight (tons)
w = mean number of wheels
p = number of days with at least 0.01 in. of precipitation per year
Plant data required to calculate the emission factor are silt content, ve-
hicle speed, mean vehicle weight, and mean number of wheels. These are
taken from the hypothetical plant data presented in Table 8-1.
Using the particle size multiplier for TSP and precipitation frequency
from Reference 1, the resultant emission factor for the haul road is:
- n a/*
-------
TABLE 8-1. PLANT AND PROCESS DATA FOR
HYPOTHETICAL FACILITY
PROCESS OPERATION -
Operating rate: 150 ton/hr
Operating hours: 1,920 hr/yr
HAUL ROAD -
Average daily traffic = 100 vehicles/day3
Average vehicle weight = 40 tons
Average number of vehicle wheels = 6
Average vehicle speed = 20 mph
Roadway length = 6.3 miles
Roadway width = 30 ft
Roadway silt content = 7.3%
TRUCK DUMP -
Material silt content =0.5%
Mean wind speed = 5 mph
Drop height = 10 ft
Material moisture content = 2%
Average truck capacity = 16 yd3
STORAGE PILE -
Storage pile silt content =2.2%
Storage pile size = 0.5 acre
FRONT-END LOADER -
Aggregate silt content = 1.6%
Mean wind speed = 5 mph
Drop height = 5 ft
Aggregate moisture content = 2%
Loader dumping capacity = 3 yd3
CUSTOMER TRAFFIC -
Road augmentation factor = 1
No. of travel lanes = 2
Surface silt content = 6%
Surface dust loading = 1,000 Ib/mile
Average vehicle weight = 30 tons
Roadway length = 0.5 miles
Average daily traffic = 120 vehicles/day01
50 round trips per day.
b Tare + load ••• 2 = 28 + 24/2 = 40 tons.
c Tare + load •=• 2 = 20 + 20/2 = 30 tons.
60 round trips per day.
143
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8.2.2 Truck Dumping
The truck dump can be considered as a batch drop operation. Thus, the
uncontrolled emission factor from Reference 1 is:
e=k(0.0018) v% n M (lb/ton) (8-3)
/Mr MU""
(2) Is)
where:
k = particle size multiplier (dimensionless)
s = material silt content (%)
U = mean wind speed (mph)
H = drop height (ft)
M = material moisture content (%)
Y = dumping device capacity (yd3)
Using the multiplier for TSP and the data shown in Table 8-1, the uncon-
trolled emission factor for the truck dump would be:
(II) (§) (!P_\
e = 0.77 (0.0018) 5 \ n l(
(!) P9
= 0.00020 lb/ton
where:
k = 0.77 for particles ^ 30 umA (see Reference 1)
s = 0.5% (given in Table 8-1)
U = 5 mph (given in Table 8-1)
H = 10 ft (given in Table 8-1)
M = 2% (given in Table 8-1)
Y = 16 yd3 (given in Table 8-1)
144
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8.2.3 Storage Pile
The TSP emission factor for wind erosion from storage piles as given
in Reference 1 is:
e = 1.7 /S
where:
s = silt content (%)
p = number of days with £ 0.01 in. of precipitation per year
f = percentage of time the unobstructed wind speed exceeds 12 mph
Using the data on silt content and estimates of p and f from Reference 1,
the resultant TSP emission factor is:
_ , 7 /2.2
- L7
= 3.2 Ib/acre/day
where:
s = 2.2% (Table 8-1)
p = 140 (Reference 1)
f = 20 (estimate)
8.2.4 Front-End Loader
For operation of the front-end loader, the appropriate uncontrolled
emission factor presented in Reference 1 is:
/s\ /U\ /H\
e = k(O.OOM) ? n(* (8-5)
S) (3
where:
k = particle size multiplier (dimensionless)
145
-------
s = material silt content (%)
U = mean wind speed (mph)
H = drop height (ft)
M = material moisture content (%)
Y = dumping device capacity (yd3)
Again, using the particle size multiplier for TSP and the operational infor-
mation provided in Table 8-1, the applicable emission factor is:
.6\
e . 0.73 (0.0018)
/2\ /3\"
(2) W
= 0.000529 Ib/ton
where:
k = 0.73 for particles 2 30 umA (see Reference 1)
s = 1.6% (see Table 11.2.3-1 of Reference 1 for crushed limestone)
U = 5 mph (given in Table 8-1)
H = 5 ft (given in Table 8-1)
M = 2% (given in Table 8-1)
Y = 3 yd3 (given in Table 8-1)
8.2.5 Customer Traffic
Finally, for customer traffic in the plant, the uncontrolled emission
factor for industrial paved roads provided in Reference 1 is:
where:
k = particle size multiplier (dimensionless)
I = industrial augmentation factor (dimensionless)
146
-------
n = number of traffic lanes (dimensionless)
s = surface material silt content (%)
L = surface dust loading (Ib/mile)
W = average vehicle weight (tons)
From the data shown in Table 8-1, the emission factor for TSP would be:
V-7
-)
=0.466 Ib/VMT
where:
k = 0.86 for particles S 30 umA (see Reference 1)
1=1 for all vehicles traveling on paved surfaces (see Reference 1,
p. 11.2.6-2)
n = 2 (given in Table 8-1)
s = 6% (given in Table 8-1)
L = 1,000 Ib/mile (given in Table 8-1)
W = 30 tons (given in Table 8-1)
8.2.6 Process Sources
The emission factors for the process sources, based on data in Refer-
ence 1, are:
Primary crushing: 0.28 Ib/ton
Secondary crushing: 0.28 Ib/ton
Tertiary crushing: 1.85 Ib/ton
Screening: 0.16 Ib/ton/screen
Conveyor transfer: 0.0034 Ib/ton/transfer point
8.2.7 Source Extents
The data in Table 8-1 can be used to calculate the following source
extents:
147
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Haul road traffic:
M = 240 x 100 vees x 6.3 S_ s 151|000 VMT/yr
Truck dump:
M = 50 *£ x 240 x 24 = 288,000
Storage piles:
M = 0.5 acre x 365 day/yr
= 182 acre day/yr
Front-end loader:
„ . 60 x 240 x 20
In- plant traffic:
„ . u, <2§i£lH x 240 SB « 0.5 ^5 . 14,400 ffl
• Process sources:
M = 150 tons/hr x 1,920 nr/yr
= 288,000 tons/yr
8.2.8 Total Plant Emissions
The above data on source extents and emission factors can be substi-
tuted into Eq. 8-1 to obtain the following emissions inventory for the hypo-
thetical plant:
TSP emissions
Source (tons/year)
Haul road traffic 669
Truck dump 0.029
Storage pile erosion 0.29
Front loader 0.076
Customer traffic 3
Primary crushing 40
Secondary crushing 40
Tertiary crushing 266
Screens 46
Transfers 3
TOTAL 1,067
148
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8.3 IDENTIFY CONTROL ALTERNATIVES
Based on the above emissions inventory, the primary focus of control
should be vehicular traffic and certain process fugitive sources (primarily
secondary and tertiary crushing and screening operations). The information
in Tables 4-1 and 4-2 can be used to assist in identifying control alterna-
tives.
Table 4-1 suggests that three methods can be used to control emissions
from unpaved roads—wet suppression, chemical stabilization, and physical
stabilization. For this hypothetical example, chemical stabilization was
selected as the most feasible means. Wet suppression was rejected because
of the difficulty in maintaining watering systems over relatively long
stretches of roads in rural areas. Chemical rather than physical stabil-
ization was selected because of the temporary nature of the facility.
The two principal means of controlling emissions from crushing and
screening operations are wet suppression and capture hoods with an asso-
ciated air pollution control device. Wet suppression was selected as the
preferred control because of difficulties associated with the operation and
maintenance of capture/collection systems on mobile crushed stone facilities.
8.4 ESTIMATE CONTROL EFFICIENCIES
Based on available performance data, a petroleum based resin was se-
lected for chemical dust suppression on the unpaved road. The data in
Table 5-2 suggest that control efficiencies of about 90% can be achieved
over short to moderate duration with such vehicles. In fact, an average
TSP control efficiency of 90% can be achieved for up to about 5,000 vehicle
passes.
Only limited test data are available on the effectiveness of wet sup-
pression systems in controlling emissions from minerals processing opera-
tions. The data in Table 6-2 indicate that control efficiencies for crush-
ing operations range from 27% to about 90%. Available data suggest that
the finer the crushing operation, the lower the efficiency. No control effi-
ciencies are specified for screens, but those controls should be at least
149
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as effective as controls for tertiary crushers. Based on these limited data,
the control efficiency estimates are:
Primary crusher: 80%
Secondary crusher: 65%
Tertiary crusher: 50%
Screens: 50%
8.5 CALCULATE COST AND COST EFFECTIVENESS
8.5.1 Chemical Stabilization of Unpaved Roads
The procedure for calculating the estimated cost and the associated
cost effectiveness of controlling vehicular emissions by chemical stabili-
zation of the unpaved haul road at the hypothetical plant is as follows.
Step 1 - Determine the Times Between Applications and the Application In-
tensity
The vehicle and road characteristics listed in Table 8-1 are similar to
those in the footnotes of Table 2-1 of Reference 2. The following appli-
cation parameters are taken from Table 2-1 of Reference 2:
Initial application intensity = 0.83 gal. of 20% solution/yd2
Reapplication intensity = 1.0 gal. of 12% solution/yd2
Application frequency = once every 55 days
Step 2 - Calculate the Number' of Annual Applications Necessary and Number
of Treated Miles "
No. of annual applications = # days/application
= 6.64 applications/yr
NO. of treated niles per year = 6.3 * 6-M
= 42 treated miles/year
150
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Step 3 - Select the Desired Program Implementation Plan
The decision Is made to purchase rather than rent equipment. The Implemen-
tation plan and associated costs are outlined In Table 8-2, Scenario 2.
Step 4 - Calculate Total Annual Cost
To annual ize the capital Investment, the capital cost shown In Table 8-2,
Scenario 2, is simply multiplied by a capital recovery factor which is cal-
culated as follows:
CRF = [1(1 + i)n] / [(1 + i)n - 1]
where:
i = annual interest rate fraction
n = number of payment years
Assuming 1 = 0.15 and n = 10 years,
(1.15)10 - 1
The annual operation and maintenance costs (C ) are calculated as follows:
CQ = $4,785/treated mile x 42 treated miles/year +
$630/actual mile x 6.3
= $205,000/year
The total annual i zed cost (C ) is:
a
= (0.199) (105,000) + 205,000 +0.5 (205,000)
= $328,000
Because the costs in Table 8-2 are based on a road width of 40 ft, it is
necessary to scale total cost by actual road width of 30 ft:
Actual total annual i zed cost = $328,000/year x
= $246,000/year
151
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TABLE 8-2. COST COMPARISON FOR TWO SELECTED IMPLEMENTATION SCENARIOS
Cost
Capital Unit O&M cost*
i nvestment $/Treated $/Actual
Alternative approach ($) mile mile
Scenario 1 - Rent where possible
to minimize capital expenditure
1. Purchase chemical and ship in truck 4,650
tanker
2. Store in contractor tank 140
3. Rent contractor grader to prepare 1,200
road
4. Take water from city line 20
5. Rent contractor truck (includes 500
labor to pump water and chemical
and apply solution)
0 57310 1,200
Scenario 2 - Buy equipment where possible
1. Purchase chemical and ship in truck 4,650
tanker
2. Store in newly purchased storage 30,000
tank
3. Prepare road with plant owned 630
grader
4. Pump water from river or lake 5,000 135
5. Apply chemical with plant owned 70,000
application truck (includes labor
to pump water and chemical and
apply solution)
105,000 4,785 630
a Plant overhead costs are included.
152
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Step 5 - Calculate Cost-Effectiveness (C*)
Cost-effectiveness is defined as:
"4
where:
C = total cost from Step 4
cl
AR = reduction in TSP emissions; i.e., the product of the uncontrolled
emission rate and the fractional efficiency of control
c* _ $246.OOP/year
~ 569 ton/year x 0.9
= $409/ton of TSP emissions reduced by chemical stabilization of
unpaved roads
8.5.2 Wet Suppression of Crushing and Screening Operations
The procedure for calculating the estimated cost and cost-effectiveness
of wet suppression applied to materials handling at the hypothetical plant
is as follows:
Step 1 - Select the Desired Program Implementation Plan
The elements of the program implementation plan are as follows:
1. Sprays are used at one primary, one secondary, and one tertiary
crusher, the truck dump to the primary crusher, two screens, and
six conveyor transfer points.
2. A centralized system with an industrial water supply is used.
3. Winterizing equipment is required.
4. The process operates 40 hr/week, 48 weeks/year, and because of op-
erating conditions, the control equipment is operated 80% of the
time that the process operates.
Step 2 - Calculate Capital Costs
The capital costs (C ) are summarized as follows:
153
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Equipment Installation Total
Type of equipment cost ($) cost ($) cost ($)
Wet suppression system 24,520 33,830 58,350
Water filter and flush 2,970 350 3,320
High pressure system for 4,630 2,290 6,920
truck dump
Shelter house 4,280 640 4,920
Winterizaticn 3.640 3,710 7.350
Total 40,040 40,820 80,860
Reference 3 was the basis for capital costs. These costs are updated from
July 1974 to January 1984 using the CE Plant Cost Index for Fabricated
Equipment. The winterization cost was estimated as 10% of other capital
equipment.
Step 3 - Calculate Annual Operating Costs
There are four categories of operating costs (C ):
1. Utilities
Electrical power - 2,880 kWh/year @ 5.5
-------
in January 1984 was based on statistics in the Monthly Labor Review. Sur-
factant costs were updated from July 1974 to January 1984 using the CE Plant
Cost Index for Pipes, Valves, and Fittings.
Step 4 - Calculate Annualized Cost
The capital recovery factor is given by:
CRF = [i(l+i)n] / [(l+i)n-l]
where:
i = annual interest rate
n = effective life
Assuming i = 0.15 and n = 10 years,
CRF = 0.199252
The annualized costs (C ) are calculated as follows:
a
= CRF (Cp) + CQ + 0.5(CQ)
where:
C = Capital investment ($)
CRF = Capital recovery factor
C = Annual operating costs ($/yr)
Substituting the cost values obtained from Steps 2 and 3,
C = 80,860 (0.199252) + 14,350 +0.5 (14,350)
a
= $37,600/year
Step 5 - Calculate Cost-Effectiveness
Cost-effectiveness is defined as:
u ~ AR
where:
Ca = total cost from Step 4
AR = reduction in TSP emissions; i.e., the product of uncontrolled
emission rate and the fractional efficiency of control
155
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The calculated emissions reductions are as follows:
Primary crusher: (40 tons/yr)(0.80) = 32
Secondary crusher: (40 tons/yr)(0.65) = 26
Tertiary crusher: (266 tons/yr)(0.5) = 133
Screens: (46 tons/yr)(0.5) = 23
Total = 214 tons/year
C* = 2147toSS/vea? = *175/ton of Isp reduced by wet suppression
y of crushing and screening operations
8.5.3 Plant Control Costs and Cost Effectiveness
The two control measures that were considered for the theoretical plant
are summarized below with their respective costs:
Cost
Annualized effectiveness
Control measure costs ($) ($/ton)
Chemical stabilization of 246,000 409
unpaved roads
Wet suppression of crushing 37,600 176
and screening operations
With the implementation of these two control measures, total TSP emissions
from this hypothetical plant would be reduced from 1,067 tons/year to
251 tons/year.
REFERENCES FOR SECTION 8
1. U.S. Environmental Protection Agency. Compilation of Air Pollution
Emission Factors (Fourth Edition). AP-42, Volume I, GPO No. 055-000-
00252-5, Office of Air Quality Planning and Standards, Research Triangle
Park, North Carolina, September 1985.
2. Cuscino, T., Jr. Cost Estimates for Selected Fugitive Dust Controls
Applied to Unpaved and Paved Roads in Iron and Steel Plants. Final
Report for Region V, U.S. Environmental Protection Agency, Chicago,
Illinois, April 1984.
3. Evans, R. J. Methods and Costs of Dust Control in Stone Crushing Op-
erations. PB-240 834, U.S. Bureau of Mines, 1C 8669, January 1975.
156
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APPENDIX A
ESTIMATION OF AIR QUALITY IMPACT/IMPROVEMENT
The identification and estimation of air quality impacts from fugitive
dust sources typically requires the use of air quality models. For purposes
of discussion, these models may be segregated conveniently into two broad
categories -- (a) source-oriented models, and (b) receptor-oriented models.
The following discussion is intended to provide a general overview of both
classes of models; for more detailed discussions, the user should consult
recent reviews readily available in the scientific literature.1-4 Prior
to discussion, it should be recognized that both source and receptor models
have a common physical basis. Both assume that mass transported from a
source to a receptor was transported with conservation of mass by atmo-
spheric dispersion of the source material.5 It should also be recognized
that the selection of an appropriate model(s) will depend upon the particular
program/study objectives and resource constraints (i.e., data, manpower,
computing facilities, etc.), as well as the user's knowledge of the model
technology available.
A.I SOURCE-ORIENTED MODELS
The "traditional" regulatory approaches have dictated that source im-
pacts be identified by dispersion (source) modeling. In this context, the
Gaussian plume model is more widely used than any other model. Stripped
to its essentials, the Gaussian model may be represented as follows:
where the parameters are:
A-l
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X (g/ra3) = concentration of pollutant in air
Q (g/s) = continuous point source strength
u (m/s) = wind speed at height H
a (m) = lateral dispersion parameter
a (m) = vertical dispersion parameter
Y (m) = lateral distance from plume center!ine
z (m) = height above ground
H (m) = final plume rise of plume above ground
As the name implies, the model predicts concentrations under the assumption
that the plume disperses in the horizontal and vertical according to a
Gaussian distribution. Other major assumptions include: (a) constant and
continuous emission rates, (b) no variations in meteorology (wind speed,
wind direction, and atmospheric stability) between source and receptor, and
(c) complete reflection of the plume from the ground surface.
The Gaussian plume concept is the basis for nearly all models in the
U.S. EPA system of UNAMAP (User's Network for Applied Modeling of Air
Pollution) models. The differences between models of the UNAMAP family are
mostly due to variations in the treatment of (a) plume rise, (b) pollutant
half-life, (c) diffusion limitations due to mixing heights, (d) source con-
figurations, and (e) dispersion coefficients to characterize plume growth.
Abstracts which summarize model capabilities of most of the current genera-
tion of UNAMAP models may be found elsewhere.6 Reasonably complete tech-
nical descriptions for each model are available in the various User's
Manuals.
For all but the crudest screening applications, the use of a dis-
persion model requires appropriate information on (a) source emission
rates, and (b) study area meteorology. In the case of stationary sources,
it is usually a fairly straightforward procedure to develop an adequate
emissions inventory. For fugitive (particularly open source) emissions,
the measures of source extent (e.g., unvegetated surface area exposed to
the wind) are often more difficult to define. As noted earlier, the
A-2
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reliability of open source emissions estimates are greatly increased if
site-specific information is collected.
In similar fashion, to make the best use of Gaussian modeling, site-
specific meterological measurements need to be made that relate closely to
pollutant dispersion.7 These include, for example, (a) continuous measure-
ments of wind speed (u) and direction (9) at two heights; (b) ambient
temperature difference (AT) between 2 and 10 m, and (c) heights of the con-
vectively mixed layer (h ) and the mechanically mixed layer (hm). Very few
programs are designed to acquire such detailed information.
Many routine modeling applications rely on data from nearby locations
such as airports, National Weather Service stations, and military installa-
tions to represent the atmospheric conditions for the area of interest.
These observations are intended primarily for aviation needs, and are not
particularly well suited to dispersion problems. The primary source for
surface and upper air meterological data is the National Climatic Data
Center (NCOC, Asheville, NC). For many long-terra or climatological appli-
cations, the meteorological conditions of a site are represented by a
stability array or "STAR" tabulation. The STAR tabulation summarizes
meteorological conditions in terms of joint frequency distributions of wind
speed, atmospheric stability class, and wind direction. This information
has been developed for many locations in the United States and is also
available from NCDC.
The principal advantage of source-oriented (dispersion) models lies
in the fact that they can be used to directly predict the impact of either
existing or proposed sources.5 Another advantage of this class of models
is that they do not require ambient air quality data, though, if available,
air quality data may be used to assign "background" pollutant levels.
Additional advantages are that the models are widely available, and have
been evaluated using many different data sets.4
The primary limitations of dispersion models relate not only to defi-
ciencies in the quality of the input data for a particular application, but
also to the ability of the Gaussian model to reproduce the important physi-
cal/chemical processes affecting transport of pollutants in the atmosphere.
A-3
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The Gaussian model will perform best under the conditions used to form the
basis for the current models. These conditions include:
Source: Low-level, continuous, nonbuoyant emissions, in simple
terrain.
Meteorology: Near neutral stability, steady, and relatively homogene-
ous wind field.
Estimate: Local, short-term, concentrations of inert pollutants.
Under those relatively simple conditions, "factor of two".agreement between
predicted and observed concentrations is probably realistic.8
Addition of complicating features to the simple dispersion case will
substantially increase the uncertainties associated with model estimates.
Complicating features include:
1. Aerodynamic wake flows of all kinds.
2. Buoyant fluid flows and accidental releases of heavy toxic gases.
3. Flows over surfaces markedly different from those represented in
the basic experiments, e.g., forests, cities, water, complex ter-
rain.
4. Dispersion in extremely stable and unstable conditions.
5. Dispersion at great downwind distances (> 10 to 20 km).
It is widely recognized that significant improvements in dispersion model-
ing will require more direct observational knowledge under these conditions.
Model users should be aware that the capabilities of the current UNAMAP
series to represent these features are based on a few special case studies.9
A.2 RECEPTOR-ORIENTED MODELS
Unlike dispersion models, receptor-oriented techniques begin with par-
ticulate measurements at a receptor(s) and then "back calculate" to estimate
source contributions. Receptor models also differ from source models in
A-4
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that they do not require a formal description of the transport metero-
logy of the area. Receptor models may be conveniently grouped into two
basic categories, microscopic, and chemical methods; these may be further
subdivided as shown in Table A-l. Each of these techniques has particular
advantages and disadvantages for problems of source apportionment, however,
none of the receptor models are predictive tools and as such have minimal
applicability in directly estimating the effectiveness of future control
strategies.5
TABLE A-l. TYPES OF RECEPTOR MODELS
1. Microscopic Methods
• Optical
• Scanning electron microscopy (SEM)
• Automated SEM
2. Chemical Methods
Enrichment factors
Time series analysis
Spatial series analysis
Chemical mass balance (CMB)
Advanced multivariate methods
A.2.1 Microscopic Methods
Microscopic methods are the older of the two classes of receptor
models. Optical methods are limited to particles greater than about 2 |jm.
One advantage of optical methods is that an experienced analyst can use
features such as color, surface texture, and optical properties to aid in
particle identification.10 A corresponding disadvantage of the method is
that the reliability of the results is then highly dependent upon individual
operator skill. A more sophisticated method, scanning electron microscopy
(SEM), can be applied to identify submicron (< 1 urn) particles. This tech-
nique may also include a determination of major chemical elements to aid in
qualitative particle type assignment. Automated SEM is the newest of the
A-5
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microscopic methods; it uses all of the same qualitative particle type
identification features as SEM but has the capability of analyzing more
particles because of its automation.2
Another advantage of microscopic methods is that they do not explicitly
require a knowledge of the chemical composition of source emissions. By
virtue of its wide use, an extensive library of "microscopic fingerprints,"
including morphological, color, and elemental features, has already been
developed.5 In general, these methods have a high source resolving capa-
bility for sources with characteristic morphological features such as wood
fiber, tire rubber, pollen, etc.
To be quantitative, microscopic methods require estimates of the
number of particles, their density and volume. It is also critical that a
sufficient number of particles be analyzed to be representative of the total
sample. A major disadvantage of microscopic methods lies in the large un-
certainties associated with determination of particle density and volume.3
Other limitations include time and cost per analysis, and lack of reliabil-
ity in identifying amorphous organic species which in many applications may
account for a large fraction of the aerosol.
A.2.2 Chemical Methods
Unlike microscopic methods, all chemical methods require knowledge of
the chemical composition of both the ambient aerosol and possible sources.2
Three of the techniques, enrichment factors, time series analysis, and spa-
tial series analysis, may be classified as relatively "simple" to apply.10
With the enrichment factor model, data on the composition of the ambient
air (i.e., at the receptor) is used with a normalizing or reference element
(usually a crustal element such as Fe, Al, or Si) to estimate the degree to
which a specific element has been "enriched" by an anthropogenic source.
This method relies heavily on the assumed background composition and is in-
applicable to complex source mixtures in which multiple sources are contri-
buting the same element.2 The method would appear to have little applica-
bility for problems concerning open dust source emissions.
Time series techniques are based on the assumption that chemical spe-
cies originating from the same source will exhibit the same temporal depen-
dence when measured at a receptor. Thus, if a set of elements at a receptor
A-6
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are temporally correlated, they are presumed to have a similar source. From
the viewpoint of source apportionment, time series correlation must be con-
sidered a qualitative technique. Nevertheless, long-term studies covering
several years can be valuable in assessing the impact of seasonally depen-
dent sources or in the implementation of control measures.2
Spatial models focus on comparison of air quality data collected for
the same time period from a number of different receptors. Qualitative
comparisons then are obtained by further comparison with the location of
known emission sources. Various forms of the spatial model include
isopleths, spatial correlations, and pollutant wind roses. In many source
apportionment applications, particularly those on the scale of a single
industrial facility, spatial variations may be of less importance than
temporal variations.
The remaining two receptor models, chemical mass balance (CMB) and
multivariable methods, generally are considered to be more resource intensive
than the other chemical methods. Under the assumption of conservation of
mass (for each chemical component), the CMB model may be expressed as:
where C. is the concentration of the chemical component i measured at the
receptor, F-. is the fraction of chemical i emitted by source j as determined
at the source, and S. is the source contribution (i.e., the ratio of the
mass contributed by source j to the total mass at the receptor.5 It is pos-
sible to calculate the source type contribution (S.) by least squares
methods1 with the following additional assumptions:
• The number of sources, p, is less than or equal to the number of
components; and
• The source compositions (F..) are linearly independent of each
other. 1J
In practice, these assumptions are not met, and considerable uncertainties
are attached to the results.1
A-7
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The CMB method is based on analysis of a single filter. The most sig-
nificant limitation to source resolution with the CMB method is the uncer-
tainty in the F.. values.2 These values can vary with time, location, raw
material, fuel type, etc. An additional limitation lies in the fact that
since many fugitive sources have similar source compositions, they cannot
be resolved as distinct sources based on the ambient concentration data.
The major difference between the CMB'and multivariate methods is that
CMB is based on the composition data of a single sample, and the multivariate
methods analyze the variability of elements measured in a large number of
samples. All.the multivariate methods are based on a correlation matrix
which shows the association between elements/samples. In one method, factor
analysis, the correlation matrix is "collapsed" to yield the minimum number
of factors required to reproduce the ambient data matrix, their relative
chemical composition, and their contribution to the mass variability.5 A
major limitation of the factor analysis technique lies in the abstract
nature of the resulting composite variables (factors) and the difficulty of
assigning source names to the variables. Various modifications to this
technique have been explored in efforts to improve the method's ability to
associate these composite variables with known sources.11'12
REFERENCES FOR APPENDIX A
1. Watson, J. G. 1984. Overview of Receptor Model Principles. Journal
of the Air Pollution Control Association. 34(6):619-623.
2. Cooper, J. A., and J. G. Watson. 1980. Receptor Oriented Methods of
Air Particulate Source Apportionment. Journal of the Air Pollution
Control Association. 30(10):1116-1125.
3. Turner, D. B. 1979. Atmospheric Dispersion Modeling: A Critical Re-
view. Journal of the Air Pollution Control Association. 29(5):502-519.
4. Hanna, S. R. 1981. Handbook on Atmospheric Diffusion Models.
ATDL-81/5, National Oceanic and Atmospheric Administration. Oak Ridge,
TN, 57 p.
5. Cooper, J. A. 1981. Chemical Mass Balance Source Apportionment Meth-
ods. Paper presented at the 74th Annual Meeting of the Air Pollution
Control Association, Philadelphia, PA.
A-8
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6. EPA. Environmental Modeling Catalogue: Abstracts of Environmental
Models. U.S. EPA Information Clearinghouse, U.S. Environmental Pro-
tection Agency, Washington, D.C. August 1982.
7. AMS. On-Site Meteorological Requirements to Characterize Diffusion
from Point Sources. Proceedings from a Workshop Held in Raleigh, NC,
January 15-17, 1980. American Meteorological Society, Boston, MA.
1980.
8. AMS. Accuracy of Dispersion Models: A Position Paper of the AMS Com-
mittee on Atmospheric Turbulence and Diffusion. Bulletin of the American
Meteorological Society. 59(8):1025-26, 1978.
9. AMS. Air Quality Modeling and the Clean Air Act: Recommendations to
EPA on Dispersion Modeling for Regulatory Applications. American
Meteorological Society, Boston, MA. 1980: NTIS, PB83-106237.
10. Core, J. E., and T. G. Pace. 1981. Receptor Models - How Great Thou
Art!(?). Paper presented at the 74th Annual Meeting of the Air Pollu-
tion Control Association, Philadelphia, PA.
11. Alpert, D. J., and P. K. Hopke. 1980. A Quantitative Determination
of Source in the Boston Urban Aerosol. Atmospheric Environment.
14:1137-1149.
12. Hopke, P. K. 1981. The Application of Target Transformation Factor
Analysis to Aerosol Source Resolution. Paper presented at the 74th
Annual Meeting of the Air Pollution Control Association, Philadelphia,
PA.
A-9
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APPENDIX B
GLOSSARY
Air Quality Models - An equation, or series of equations which predict a
source impact on air quality.
Annualized Cost - The control technique cost (S/yr) calculated as annual
cost over the useful life of the equipment (or application). The
annualized cost is a sum of the annualized purchase and installation
cost (i.e. capital costs) and the annual maintenance and operating
costs.
Application Frequency - Number of applications of a control measure to a
specific source per unit time; equivalently, the inverse of time be-
tween two applications.
Application Intensity - Volume of water or chemical solution applied per
unit area of the treated surface.
Canopy Hood - A receiving hood located above the source of emissions in-
tended to capture the emissions as the emissions are directed upward
due to thermal gradients (e.g. a canopy hood for capturing furnace
charging emissions).
Capital Recovery Factor - The factor which is used to annualize capital
investment to obtain the annualized capital cost. The capital re-
covery factor is a function of annual interest rate and the total
number of payment years.
Capture Device - A system for capturing emissions generated by a process
or materials handling operation (e.g. receiving hood, side draft
hood).
B-l
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Capture Efficiency - The efficiency at which an air pollution control sys-
tem captures fugitive emissions (e.g. hood). That is, the mass emis-
sions captured divided by the total uncontrolled emissions generated
by the source times a factor of 100.
Close Capture Hood - A receiving hood located In close proximity to the
source of emissions.
Collection Device - A gas cleaning device for removing air pollutants from
the air stream passing through it (e.g. baghouse, scrubber, electro-
stati c precipitation).
Collection Efficiency - The efficiency of an air pollution collection de-
vice (e.g. baghouse). That is, the mass emissions collected divided
by the mass emissions entering the device times a factor of 100.
Collection Hood - A hood designed to capture particulate matter emissions
by inducing a draft on the emission plume, thereby pulling the emis-
sions into the hood.
Control Efficiency - Percent decrease in controlled emissions from the un-
controlled state.
Cost-Effectiveness - The cost of control per unit mass of reduced particu-
late emissions.
Dilution Ratio - Ratio of the number of parts of chemical to the number of
parts of solution, expressed in percent (e.g., one part of chemical to
four parts of water corresponds to a 20% solution).
Dry Sieving - The sieving of oven-dried aggregate by passing it through a
series of screens of descending opening size.
Duration of Storage - The average time that a unit of aggregate material
remains in open storage, or the average pile turnover time.
B-2
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Oust Suppressant - Mater or chemical solution which, when applied to an
aggregate material, binds suspendable participate to larger particles.
Emission Factor - An estimate of the mass of uncontrolled emissions re-
leased to the atmosphere per unit of source extent (e.g. kg/ton
product).
Emissions Inventory - A listing and classification of all sources of emis-
sions, and the quantity of emissions generated for a specific geograph-
ic area or facility.
Emission Rate - Mass of emissions generated per unit time (e.g. kilogram
per hour).
Enclosures - A common preventive measure for the control of fugitive partic-
ulate matter emissions which involves either totally or partially en-
closing the source to inhibit or contain emissions.
Erosion Potential - Total quantity of erodible particles, in any size range,
present on the surface (per unit area} prior to the onset of erosion.
Exposed Area - Outdoor ground area subject to the action of wind and pro-
tected by little or no vegetation.
Exposure Profiling Method - A method for quantifying fugitive emissions
which involves the isokinetic measurement of airborne pollutant imme-
diately downwind of the source by means of simultaneous multipoint
sampling over the effective plume cross section.
Fine Particulate (FP) - Particulate matter less than or equal to 2.5 ym
in aerodynamic diameter.
Fugitive Oust - Solid particles generated by the action of wind or machinery
which are not emitted from a stack, duct or flue.
B-3
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Fugitive Emissions - Emissions not originating from a stack, duct, or flue.
HVLV Local Exhaust - A high velocity, low volume induced draft hood located
right at the source to capture the emissions.
Inhalable Particulate (IP) - Particulate matter less than or equal to 15 ^m
aerodynamic diameter.
Load-in - The addition of material to a storage pile.
Load-out - The removal of ma'srial from a storage pile.
Materials Handling - The receiving and transport of raw, intermediate and
waste materials, including barge/railcar unloading, conveyor transport
and associated conveyor transfer and screening stations.
Moisture Content - The mass portion of an aggregate sample consisting of
unbound moisture as determined from weight loss in oven drying.
Open Oust Sources - Sources of fugitive emissions that entail generation
of particulate matter by the forces of wind or machinery acting on
exposed (i.e. open) materials where no physical or chemical change
occurs to the particle-generating material.
Partially Enclosed Materials Handling Operations - Partially enclosed
sources which generate fugitive emission during the storage or trans-
fer of materials to or from a process operation.
Particle Diameter, Aerodynamic - The diameter of a hypothetical sphere of
unit density (1 g/cm3) having the same terminal settling velocity as
the particle in question, regardless of its geometric size, shape and
true density.
Plume Aftertreatment - The application of a fine water spray or fog to the
suspended participate plume near the source to capture and agglomerate
the particles by inertia! impaction so that gravitational settling can
occur.
B-4
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PM-10 - Parti oil ate matter less than or equal to 10 Aim in aerodynamic
diameter.
Preventive Measures • Techniques for controlling fugitive particulate emis-
sions which prevent the creation and/or release of particulate matter
(e.g. wet suppression, stabilization of unpaved surfaces, cleaning of
paved surfaces).
Process Sources - Sources of fugitive emissions associated with industrial
operations that alter the chemical or physical characteristics of a
feed material.
Quasi-Stack Method - A method for quantifying fugitive emissions which in-
volves capturing the entire emissions stream with enclosures or hoods
and then applying conventional source testing techniques to the con-
fined flow.
Receiving Hood - A hood designed to capture particulate emissions which are
directed at the hood from the source by thermal or mechanical forces.
Receptor-Oriented Air Quality Model (Receptor Model) - An air quality model
which uses chemical analysis at receptors (i.e. ambient monitors), to
statistically infer the separate contribution from each of the sources
of the emissions.
Respirable Particulate (RP) - Particulate matter less than or equal to about
3.5 (j"i aerodynamic diameter, as measured with a 10-mm Dorr-Oliver cy-
clone precollector.
Road, Paved - A roadway constructed of rigid surface materials, such as
asphalt, cement, concrete, and brick.
Road, Unpaved - A roadway constructed of nonrigid surface materials such as
dirt, gravel (crushed stone or slag), and oil and chip surfaces.
Road Surface Dust Loading - The mass of loose surface dust on a paved road-
way, per length of roadway, as determined by dry vacuuming.
B-5
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Road Surface Material - Loose material present on the surface of an unpaved
road.
Roof Monitor Method - A method for quantifying fugitive emissions which
involves measurement of mass concentrations and air flows at multiple
points in well defined building openings such as roof monitors, ceil-
ing vent, or windows.
Side Draft Hood - A type of capture device which operates by inducing a
sideways draft thereby pulling emissions into the hood.
Silt Content - The mass porticn of an aggregate sample smaller than 75 mi-
crometers in diameter as determined by dry sieving.
Source Extent - The measure of the level of source activity (e.g. tons
product per year, tons feed per day, BTU per hour).
Source-Oriented Air Quality Models (Dispersion Models) - An air quality
model which predicts a source's impact on air quality by using a
series of predictive equations to model the dispersion of the plume
from the source.
Spray System - A device for applying a liquid dust suppressant in the form
of droplets to an aggregate material for the purposes of controlling
the generation of dust.
Stabilization - The use of chemical dust suppressants for the control of
fugitive particulate emissions from open dust sources (e.g. unpaved
roads) or material storage piles.
Storage Pile Activities - Processes associated with aggregate storage piles,
specifically, load-in, vehicular traffic around storage piles, wind
erosion from storage piles, and load-out.
Surface Cleaning - A method for reducing the surface loading of particulates
on paved surfaces to reduce particulate emissions (e.g. street cleaning)
B-6
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Total Participate (TP) - Participate matter of all sizes as collected by iso-
kinetic sampling.
Total Suspended Particulate (TSP) - Participate matter measured by a high
volume sampler with an inlet 50% cutoff 30-50 jzm in aerodynamic dia-
meter.
Upwind-Downwind Method - A method of quantifying fugitive emissions which
involves the measurement of air quality upwind and downwind of the
source under known meteorological conditions, followed by "back-
calculation" of source emission rates using atmospheric dispersion
equati ons.
Vehicle, Heavy-Duty - A motor vehicle with a gross vehicle travelling weight
exceeding 30 tons.
Vehicle, Light-Duty - A motor vehicle with a gross vehicle travelling weight
of less than or equal to 3 tons.
Vehicles, Medium-Duty - A motor vehicle with a gross vehicle travelling
weight of greater than 3 tons, but less than 30 tons.
Wet Suppression - The application of water or a water solution of a chemical
agent to the surface of the material producing emissions to inhibit the
generation of particulate matter emissions.
Wind Fences/Barriers - Man-made structures or vegetative barriers used to
control emissions from open sources (e.g. material storage piles) by
providing an area of reduced wind velocity at the source.
Wind Tunnel Method - A method for measuring wind erosion emissions which
involves using a portable pull-through wind tunnel with an open-floored
test section. The portable wind tunnel is placed directly over the
surface to be tested, air is drawn through the tunnel, and emissions
are measured by an isokinetic probe fitted at the downstream end of
the tunnel.
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1 REPORT NO. 2.
EPA-600/8- 86-023
4. TITLE AND SUBTITLE
Identification, Assessment, and Control of Fugitive
Particulate Emissions
7. AUTHORIS)
Chatten Cowherd, Jr. , and John S. Kinsey
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Midwest Research Institute
425 Volker Boulevard
Kansas City, Missouri 64110
12. SPONSORING AGENCY NAME AND ADDRESS
EPA, Office of Research and Development
Air and Energy Engineering Research Laboratory
Research Triangle Park, NC 27711
3. RECIPIENT'S ACCESSION NO.
S. REPORT DATE
August 1986
6. PERFORMING ORGANIZATION CODE
B. PERFORMING ORGANIZATION REPORT NO.
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-02-3922
13. TYPE OF REPORT AND PERIOD COVERED
Final; 4/83-4/86
14. SPONSORING AGENCY CODE
EPA/600/13
15. SUPPLEMENTARY NOTES AEERL project officer is Dale L. Harmon, Mail Drop 61, 919/541-
2429.
is. ABSTRACT The technical manual, designed to assist national, state, and local control
agency personnel and industry personnel in evaluating fugitive emission control plans
and in developing cost-effective control strategies, describes the identification,
TECHNICAL REPORT DATA
(f lease read Inunctions on the reverse before completing)
assessment, and control of fugitive particulate emissions. The manual's organiza-
tional structure follows the steps to be taken in developing a cost-effective control
strategy for fugitive particulate emissions. The procedural steps are the same
whether the sources of interest are within a specific industrial facility or distribu-
ted over an air quality control jurisdiction. The manual summarizes the quality and
extent of published performance data for control systems applicable to open dust
sources and process sources. The scheme developed to rate performance data re-
flects the extent to which a control efficiency value is based on mass emission meas-
urement and reported in enough detail for adequate validation. In addition to presen-
ting a cost analysis methodology, the manual identifies primary cost elements and
sources of cost data and presents a fully worked industrial example of cost-effective
control strategy development.
17.
KEY WORDS AND DOCUMENT ANALYSIS
a. DESCRIPTORS
Pollution Leakage
Assessments
Particles
Dust
Aerosols
Processing
13. DISTRIBUTION STATEMENT
Release to Public
b.lOENTIFIERS/OPEN ENDED TERMS
Pollution Control
Stationary Sources
Fugitive Emissions
Particulate
19. SECURITY CLASS (This Report)
Unclassified
30. SECURITY CLASS (Thu page/
Unclassified
c. COSATI Field/Group
13B
14B
14G
11G
07D
14H
21. NO OF PAGES
180
22. PRICE
1
EPA Form 2220-1 O-73)
B-8
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